An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment

NASA Astrophysics Data System (ADS)

Smitha, P. S.; Narasimhan, B.; Sudheer, K. P.; Annamalai, H.

2018-01-01

Regional climate models (RCMs) are used to downscale the coarse resolution General Circulation Model (GCM) outputs to a finer resolution for hydrological impact studies. However, RCM outputs often deviate from the observed climatological data, and therefore need bias correction before they are used for hydrological simulations. While there are a number of methods for bias correction, most of them use monthly statistics to derive correction factors, which may cause errors in the rainfall magnitude when applied on a daily scale. This study proposes a sliding window based daily correction factor derivations that help build reliable daily rainfall data from climate models. The procedure is applied to five existing bias correction methods, and is tested on six watersheds in different climatic zones of India for assessing the effectiveness of the corrected rainfall and the consequent hydrological simulations. The bias correction was performed on rainfall data downscaled using Conformal Cubic Atmospheric Model (CCAM) to 0.5° × 0.5° from two different CMIP5 models (CNRM-CM5.0, GFDL-CM3.0). The India Meteorological Department (IMD) gridded (0.25° × 0.25°) observed rainfall data was considered to test the effectiveness of the proposed bias correction method. The quantile-quantile (Q-Q) plots and Nash Sutcliffe efficiency (NSE) were employed for evaluation of different methods of bias correction. The analysis suggested that the proposed method effectively corrects the daily bias in rainfall as compared to using monthly factors. The methods such as local intensity scaling, modified power transformation and distribution mapping, which adjusted the wet day frequencies, performed superior compared to the other methods, which did not consider adjustment of wet day frequencies. The distribution mapping method with daily correction factors was able to replicate the daily rainfall pattern of observed data with NSE value above 0.81 over most parts of India. Hydrological simulations forced using the bias corrected rainfall (distribution mapping and modified power transformation methods that used the proposed daily correction factors) was similar to those simulated by the IMD rainfall. The results demonstrate that the methods and the time scales used for bias correction of RCM rainfall data have a larger impact on the accuracy of the daily rainfall and consequently the simulated streamflow. The analysis suggests that the distribution mapping with daily correction factors can be preferred for adjusting RCM rainfall data irrespective of seasons or climate zones for realistic simulation of streamflow.

Systematic errors in the simulation of the Asian summer monsoon: the role of rainfall variability on a range of time and space scales

NASA Astrophysics Data System (ADS)

Martin, Gill; Levine, Richard; Klingaman, Nicholas; Bush, Stephanie; Turner, Andrew; Woolnough, Steven

2015-04-01

Despite considerable efforts worldwide to improve model simulations of the Asian summer monsoon, significant biases still remain in climatological seasonal mean rainfall distribution, timing of the onset, and northward and eastward extent of the monsoon domain (Sperber et al., 2013). Many modelling studies have shown sensitivity to convection and boundary layer parameterization, cloud microphysics and land surface properties, as well as model resolution. Here we examine the problems in representing short-timescale rainfall variability (related to convection parameterization), problems in representing synoptic-scale systems such as monsoon depressions (related to model resolution), and the relationship of each of these with longer-term systematic biases. Analysis of the spatial distribution of rainfall intensity on a range of timescales ranging from ~30 minutes to daily, in the MetUM and in observations (where available), highlights how rainfall biases in the South Asian monsoon region on different timescales in different regions can be achieved in models through a combination of the incorrect frequency and/or intensity of rainfall. Over the Indian land area, the typical dry bias is related to sub-daily rainfall events being too infrequent, despite being too intense when they occur. In contrast, the wet bias regions over the equatorial Indian Ocean are mainly related to too frequent occurrence of lower-than-observed 3-hourly rainfall accumulations which result in too frequent occurrence of higher-than-observed daily rainfall accumulations. This analysis sheds light on the model deficiencies behind the climatological seasonal mean rainfall biases that many models exhibit in this region. Changing physical parameterizations alters this behaviour, with associated adjustments in the climatological rainfall distribution, although the latter is not always improved (Bush et al., 2014). This suggests a more complex interaction between the diabatic heating and the large-scale circulation than is indicated by the intensity and frequency of rainfall alone. Monsoon depressions and low pressure systems are important contributors to monsoon rainfall over central and northern India, areas where MetUM climate simulations typically show deficient monsoon rainfall. Analysis of MetUM climate simulations at resolutions ranging from N96 (~135km) to N512 (~25km) suggests that at lower resolution the numbers and intensities of monsoon depressions and low pressure systems and their associated rainfall are very low compared with re-analyses/observations. We show that there are substantial increases with horizontal resolution, but resolution is not the only factor. Idealised simulations, either using nudged atmospheric winds or initialised coupled hindcasts, which improve (strengthen) the mean state monsoon and cyclonic circulation over the Indian peninsula, also result in a substantial increase in monsoon depressions and associated rainfall. This suggests that a more realistic representation of monsoon depressions is possible even at lower resolution if the larger-scale systematic error pattern in the monsoon is improved.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; ...

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ˜25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Simulated transient thermal infrared emissions of forest canopies during rainfall events

NASA Astrophysics Data System (ADS)

Ballard, Jerrell R.; Hawkins, William R.; Howington, Stacy E.; Kala, Raju V.

2017-05-01

We describe the development of a centimeter-scale resolution simulation framework for a theoretical tree canopy that includes rainfall deposition, evaporation, and thermal infrared emittance. Rainfall is simulated as discrete raindrops with specified rate. The individual droplets will either fall through the canopy and intersect the ground; adhere to a leaf; bounce or shatter on impact with a leaf resulting in smaller droplets that are propagated through the canopy. Surface physical temperatures are individually determined by surface water evaporation, spatially varying within canopy wind velocities, solar radiation, and water vapor pressure. Results are validated by theoretical canopy gap and gross rainfall interception models.

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

Accounting for interannual variability: A comparison of options for water resources climate change impact assessments

NASA Astrophysics Data System (ADS)

Johnson, Fiona; Sharma, Ashish

2011-04-01

Empirical scaling approaches for constructing rainfall scenarios from general circulation model (GCM) simulations are commonly used in water resources climate change impact assessments. However, these approaches have a number of limitations, not the least of which is that they cannot account for changes in variability or persistence at annual and longer time scales. Bias correction of GCM rainfall projections offers an attractive alternative to scaling methods as it has similar advantages to scaling in that it is computationally simple, can consider multiple GCM outputs, and can be easily applied to different regions or climatic regimes. In addition, it also allows for interannual variability to evolve according to the GCM simulations, which provides additional scenarios for risk assessments. This paper compares two scaling and four bias correction approaches for estimating changes in future rainfall over Australia and for a case study for water supply from the Warragamba catchment, located near Sydney, Australia. A validation of the various rainfall estimation procedures is conducted on the basis of the latter half of the observational rainfall record. It was found that the method leading to the lowest prediction errors varies depending on the rainfall statistic of interest. The flexibility of bias correction approaches in matching rainfall parameters at different frequencies is demonstrated. The results also indicate that for Australia, the scaling approaches lead to smaller estimates of uncertainty associated with changes to interannual variability for the period 2070-2099 compared to the bias correction approaches. These changes are also highlighted using the case study for the Warragamba Dam catchment.

Comparison of different types of medium scale field rainfall simulators

NASA Astrophysics Data System (ADS)

Dostál, Tomáš; Strauss, Peter; Schindewolf, Marcus; Kavka, Petr; Schmidt, Jürgen; Bauer, Miroslav; Neumann, Martin; Kaiser, Andreas; Iserloh, Thomas

2015-04-01

Rainfall simulators are used in numerous experiments to study runoff and soil erosion characteristics. However, they usually differ in their construction details, rainfall generation, plot size and other technical parameters. As field experiments using medium to large scale rainfall simulators (plot length 3 - 8 m) are very much time and labor consuming, close cooperation of individual teams and comparability of results is highly desirable to enlarge the database of results. Two experimental campaigns were organized to compare three field rainfall simulators of similar scale (plot size), but with different technical parameters. The results were then compared, to identify parameters that are crucial for soil loss and surface runoff formation and test if results from individual devices can be reliably compared. The rainfall simulators compared were: field rainfall simulator of CTU Prague (the Czech Republic) (Kavka et al., 2012; EGU2015-11025), field simulator of BAW (Austria) (Strauss et al., 2002) and field simulator of TU Bergakademie Freiberg (Germany) (Schindewolf & Schmidt 2012). The device of CTU Prague is usually applied to a plot size of 9,5 x 2 m employing 4 nozzles SS Full Jet 40WSQ mounted on folding arm, working pressure is 0.8 bar, height of nozzles is 2.65 m. The intensity of rainfall is regulated electronically, which leaves the nozzle opened only for certain time. The rainfall simulator of BAW is constructed as a modular system, which is usually applied for a length of 5 m (area 2 x 5 m), using 6 nozzles SS Full Jet 40WSQ. Usual working pressure is 0.25 bar. Elevation of nozzles is 2.6 m. The intensity of rainfall is regulated electronically, which leaves the nozzle opened only for certain time. The device of TU Bergakademie Freiberg is also standard modular system, working usually with a plot size of 3 x 1 m, using 3 oscillating VeeJet 80/100 nozzles with an usual operating pressure of 0.5 bar. Intensity is regulated by the frequency of sweeps above the experimental plot. Comparison was done during two independent campaigns, where always two devices were present. Rainfall intensity for the experiments varied between 40 to 60 mm/h. Mutual comparison was carried out between the CTU Prague and TU Freiberg RSs at plot size of 3 x 1 m and Between CTU Prague and BAW RSs at plot size of 5 x 2 m. In general, the experiments revealed a significant effect of potential heterogeneities at the experimental plots and an effect of raindrop energy on both surface runoff formation and mainly soil loss. Therefore, coordination of methodology of the experiments and careful control of initial conditions seem to be a crucial point for comparability of results from individual devices. Detailed results will be presented on the poster. The research has been supported by the research grants SGS14/180/OHK1/3T/11, QJ1230056 and 7AMB14AT020. References Kavka, P., Davidová, T., Janotová, B., Bauer, M. a Dostál, T. 2012. Mobilní dešťový simulátor.(in Czech), Stavební obzor. 8, 2012. Schindewolf, M. & J. Schmidt (2012): Parameterization of the EROSION 2D/3D soil erosion model using a small-scale rainfall simulator and upstream runoff simulation, Catena 91, pp. 47-55, DOI: 10.1016/j.catena.2011.01.007 Strauss P., J.Pitty, M.Pfeffer, A. Mentler (2000): Rainfall Simulation for Outdoor Experiments. In: P. Jamet, J. Cornejo(eds.): Current research methods to assess the environmental fate of pesticides. pp. 329-333, INRA Editions.

Simulating the complex output of rainfall and hydrological processes using the information contained in large data sets: the Direct Sampling approach.

NASA Astrophysics Data System (ADS)

Oriani, Fabio

2017-04-01

The unpredictable nature of rainfall makes its estimation as much difficult as it is essential to hydrological applications. Stochastic simulation is often considered a convenient approach to asses the uncertainty of rainfall processes, but preserving their irregular behavior and variability at multiple scales is a challenge even for the most advanced techniques. In this presentation, an overview on the Direct Sampling technique [1] and its recent application to rainfall and hydrological data simulation [2, 3] is given. The algorithm, having its roots in multiple-point statistics, makes use of a training data set to simulate the outcome of a process without inferring any explicit probability measure: the data are simulated in time or space by sampling the training data set where a sufficiently similar group of neighbor data exists. This approach allows preserving complex statistical dependencies at different scales with a good approximation, while reducing the parameterization to the minimum. The straights and weaknesses of the Direct Sampling approach are shown through a series of applications to rainfall and hydrological data: from time-series simulation to spatial rainfall fields conditioned by elevation or a climate scenario. In the era of vast databases, is this data-driven approach a valid alternative to parametric simulation techniques? [1] Mariethoz G., Renard P., and Straubhaar J. (2010), The Direct Sampling method to perform multiple-point geostatistical simulations, Water. Rerous. Res., 46(11), http://dx.doi.org/10.1029/2008WR007621 [2] Oriani F., Straubhaar J., Renard P., and Mariethoz G. (2014), Simulation of rainfall time series from different climatic regions using the direct sampling technique, Hydrol. Earth Syst. Sci., 18, 3015-3031, http://dx.doi.org/10.5194/hess-18-3015-2014 [3] Oriani F., Borghi A., Straubhaar J., Mariethoz G., Renard P. (2016), Missing data simulation inside flow rate time-series using multiple-point statistics, Environ. Model. Softw., vol. 86, pp. 264 - 276, http://dx.doi.org/10.1016/j.envsoft.2016.10.002

Realism of Indian Summer Monsoon Simulation in a Quarter Degree Global Climate Model

NASA Astrophysics Data System (ADS)

Salunke, P.; Mishra, S. K.; Sahany, S.; Gupta, K.

2017-12-01

This study assesses the fidelity of Indian Summer Monsoon (ISM) simulations using a global model at an ultra-high horizontal resolution (UHR) of 0.25°. The model used was the atmospheric component of the Community Earth System Model version 1.2.0 (CESM 1.2.0) developed at the National Center for Atmospheric Research (NCAR). Precipitation and temperature over the Indian region were analyzed for a wide range of space and time scales to evaluate the fidelity of the model under UHR, with special emphasis on the ISM simulations during the period of June-through-September (JJAS). Comparing the UHR simulations with observed data from the India Meteorological Department (IMD) over the Indian land, it was found that 0.25° resolution significantly improved spatial rainfall patterns over many regions, including the Western Ghats and the South-Eastern peninsula as compared to the standard model resolution. Convective and large-scale rainfall components were analyzed using the European Centre for Medium Range Weather Forecast (ECMWF) Re-Analysis (ERA)-Interim (ERA-I) data and it was found that at 0.25° resolution, there was an overall increase in the large-scale component and an associated decrease in the convective component of rainfall as compared to the standard model resolution. Analysis of the diurnal cycle of rainfall suggests a significant improvement in the phase characteristics simulated by the UHR model as compared to the standard model resolution. Analysis of the annual cycle of rainfall, however, failed to show any significant improvement in the UHR model as compared to the standard version. Surface temperature analysis showed small improvements in the UHR model simulations as compared to the standard version. Thus, one may conclude that there are some significant improvements in the ISM simulations using a 0.25° global model, although there is still plenty of scope for further improvement in certain aspects of the annual cycle of rainfall.

Synthetic generation of spatially high resolution extreme rainfall in Japan using Monte Carlo simulation with AMeDAS analyzed rainfall data sets

NASA Astrophysics Data System (ADS)

Haruki, W.; Iseri, Y.; Takegawa, S.; Sasaki, O.; Yoshikawa, S.; Kanae, S.

2016-12-01

Natural disasters caused by heavy rainfall occur every year in Japan. Effective countermeasures against such events are important. In 2015, a catastrophic flood occurred in Kinu river basin, which locates in the northern part of Kanto region. The remarkable feature of this flood event was not only in the intensity of rainfall but also in the spatial characteristics of heavy rainfall area. The flood was caused by continuous overlapping of heavy rainfall area over the Kinu river basin, suggesting consideration of spatial extent is quite important to assess impacts of heavy rainfall events. However, the spatial extent of heavy rainfall events cannot be properly measured through rainfall measurement by rain gauges at observation points. On the other hand, rainfall measurements by radar observations provide spatially and temporarily high resolution rainfall data which would be useful to catch the characteristics of heavy rainfall events. For long term effective countermeasure, extreme heavy rainfall scenario considering rainfall area and distribution is required. In this study, a new method for generating extreme heavy rainfall events using Monte Carlo Simulation has been developed in order to produce extreme heavy rainfall scenario. This study used AMeDAS analyzed precipitation data which is high resolution grid precipitation data made by Japan Meteorological Agency. Depth area duration (DAD) analysis has been conducted to extract extreme rainfall events in the past, considering time and spatial scale. In the Monte Carlo Simulation, extreme rainfall event is generated based on events extracted by DAD analysis. Extreme heavy rainfall events are generated in specific region in Japan and the types of generated extreme heavy rainfall events can be changed by varying the parameter. For application of this method, we focused on Kanto region in Japan. As a result, 3000 years rainfall data are generated. 100 -year probable rainfall and return period of flood in Kinu River Basin (2015) are obtained using generated data. We compared 100-year probable rainfall calculated by this method with other traditional method. New developed method enables us to generate extreme rainfall events considering time and spatial scale and produce extreme rainfall scenario.

On the dust load and rainfall relationship in South Asia: an analysis from CMIP5

NASA Astrophysics Data System (ADS)

Singh, Charu; Ganguly, Dilip; Dash, S. K.

2018-01-01

This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system.

A simple stochastic rainstorm generator for simulating spatially and temporally varying rainfall

NASA Astrophysics Data System (ADS)

Singer, M. B.; Michaelides, K.; Nichols, M.; Nearing, M. A.

2016-12-01

In semi-arid to arid drainage basins, rainstorms often control both water supply and flood risk to marginal communities of people. They also govern the availability of water to vegetation and other ecological communities, as well as spatial patterns of sediment, nutrient, and contaminant transport and deposition on local to basin scales. All of these landscape responses are sensitive to changes in climate that are projected to occur throughout western North America. Thus, it is important to improve characterization of rainstorms in a manner that enables statistical assessment of rainfall at spatial scales below that of existing gauging networks and the prediction of plausible manifestations of climate change. Here we present a simple, stochastic rainstorm generator that was created using data from a rich and dense network of rain gauges at the Walnut Gulch Experimental Watershed (WGEW) in SE Arizona, but which is applicable anywhere. We describe our methods for assembling pdfs of relevant rainstorm characteristics including total annual rainfall, storm area, storm center location, and storm duration. We also generate five fitted intensity-duration curves and apply a spatial rainfall gradient to generate precipitation at spatial scales below gauge spacing. The model then runs by Monte Carlo simulation in which a total annual rainfall is selected before we generate rainstorms until the annual precipitation total is reached. The procedure continues for decadal simulations. Thus, we keep track of the hydrologic impact of individual storms and the integral of precipitation over multiple decades. We first test the model using ensemble predictions until we reach statistical similarity to the input data from WGEW. We then employ the model to assess decadal precipitation under simulations of climate change in which we separately vary the distribution of total annual rainfall (trend in moisture) and the intensity-duration curves used for simulation (trends in storminess). We demonstrate the model output through spatial maps of rainfall and through statistical comparisons of relevant parameters and distributions. Finally, discuss how the model can be used to understand basin-scale hydrology in terms of soil moisture, runoff, and erosion.

High-Resolution Simulation of Hurricane Bonnie (1998). Part 1; The Organization of Vertical Motion

NASA Technical Reports Server (NTRS)

Braun, Scott A.; Montgomery, Michael T.; Pu, Zhaoxia

2003-01-01

Hurricanes are well known for their strong winds and heavy rainfall, particularly in the intense rainband (eyewall) surrounding the calmer eye of the storm. In some hurricanes, the rainfall is distributed evenly around the eye so that it has a donut shape on radar images. In other cases, the rainfall is concentrated on one side of the eyewall and nearly absent on the other side and is said to be asymmetric. This study examines how the vertical air motions that produce the rainfall are distributed within the eyewall of an asymmetric hurricane and the factors that cause this pattern of rainfall. We use a sophisticated numerical forecast model to simulate Hurricane Bonnie, which occurred in late August of 1998 during a special NASA field experiment designed to study hurricanes. The simulation results suggest that vertical wind shear (a rapid change in wind speed or direction with height) caused the asymmetric rainfall and vertical air motion patterns by tilting the hurricane vortex and favoring upward air motions in the direction of tilt. Although the rainfall in the hurricane eyewall may surround more than half of the eye, the updrafts that produce the rainfall are concentrated in very small-scale, intense updraft cores that occupy only about 10% of the eyewall area. The model simulation suggests that the timing and location of individual updraft cores are controlled by intense, small-scale vortices (regions of rapidly swirling flow) in the eyewall and that the updrafts form when the vortices encounter low-level air moving into the eyewall.

Censored rainfall modelling for estimation of fine-scale extremes

NASA Astrophysics Data System (ADS)

Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

2018-01-01

Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

Rainfall–runoff model parameter estimation and uncertainty evaluation on small plots

EPA Science Inventory

Four seasonal rainfall simulations in 2009 and 2010were applied to a field containing 36 plots (0.75 × 2 m each), resulting in 144 runoff events. In all simulations, a constant rate of rainfall was applied then halted 60min after initiation of runoff, with plot-scale monitoring o...

Toward an operational tool to simulate green roof hydrological impact at the basin scale: a new version of the distributed rainfall-runoff model Multi-Hydro.

PubMed

Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel

2016-10-01

Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.

Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.

2003-12-01

The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present‐Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

PubMed Central

Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-01-01

Abstract Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large‐scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large‐scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large‐scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large‐scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale‐aware parameterizations, but also reveal unrecognized trade‐offs from the entanglement of precipitation frequency and total amount. PMID:29861837

Scale-dependency of effective hydraulic conductivity on fire-affected hillslopes

NASA Astrophysics Data System (ADS)

Langhans, Christoph; Lane, Patrick N. J.; Nyman, Petter; Noske, Philip J.; Cawson, Jane G.; Oono, Akiko; Sheridan, Gary J.

2016-07-01

Effective hydraulic conductivity (Ke) for Hortonian overland flow modeling has been defined as a function of rainfall intensity and runon infiltration assuming a distribution of saturated hydraulic conductivities (Ks). But surface boundary condition during infiltration and its interactions with the distribution of Ks are not well represented in models. As a result, the mean value of the Ks distribution (KS¯), which is the central parameter for Ke, varies between scales. Here we quantify this discrepancy with a large infiltration data set comprising four different methods and scales from fire-affected hillslopes in SE Australia using a relatively simple yet widely used conceptual model of Ke. Ponded disk (0.002 m2) and ring infiltrometers (0.07 m2) were used at the small scales and rainfall simulations (3 m2) and small catchments (ca 3000 m2) at the larger scales. We compared KS¯ between methods measured at the same time and place. Disk and ring infiltrometer measurements had on average 4.8 times higher values of KS¯ than rainfall simulations and catchment-scale estimates. Furthermore, the distribution of Ks was not clearly log-normal and scale-independent, as supposed in the conceptual model. In our interpretation, water repellency and preferential flow paths increase the variance of the measured distribution of Ks and bias ponding toward areas of very low Ks during rainfall simulations and small catchment runoff events while areas with high preferential flow capacity remain water supply-limited more than the conceptual model of Ke predicts. The study highlights problems in the current theory of scaling runoff generation.

Convective Systems Over the South China Sea: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Shie, C.-L.; Johnson, D.; Simpson, J.; Braun, S.; Johnson, R.; Ciesielski, P. E.; Starr, David OC. (Technical Monitor)

2002-01-01

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convective storms and air pattern changes associated with monsoons over the South China Sea region. SCSMEX also provided rainfall estimates which allows for comparisons with those obtained from the Tropical Rainfall Measuring Mission (TRMM), a low earth orbit satellite designed to measure rainfall from space. The Goddard Cumulus Ensemble (GCE) model (with 1-km grid size) is used to understand and quantify the precipitation processes associated with the summer monsoon over the South China Sea. This is the first (loud-resolving model used to simulate precipitation processes in this particular region. The GCE-model results captured many of the observed precipitation characteristics because it used a fine grid size. For example, the temporal variation of the simulated rainfall compares quite well to the sounding-estimated rainfall variation. The time and domain-averaged temperature (heating/cooling) and water vapor (drying/ moistening) budgets are in good agreement with observations. The GCE-model-simulated rainfall amount also agrees well with TRMM rainfall data. The results show there is more evaporation from the ocean surface prior to the onset of the monsoon than after the on-et of monsoon when rainfall increases. Forcing due to net radiation (solar heating minus longwave cooling) is responsible for about 25% of the precipitation in SCSMEX The transfer of heat from the ocean into the atmosphere does not contribute significantly to the rainfall in SCSMEX. Model sensitivity tests indicated that total rain production is reduced 17-18% in runs neglecting the ice phase. The SCSMEX results are compared to other GCE-model-simulated weather systems that developed during other field campaigns (i.e., west Pacific warm pool region, eastern Atlantic region and central USA). Large-scale forcing vie temperature and water vapor tendency, is the major energy source for net condensation in the tropical cases. The effects of large-scale cooling exceed that of large-scale moistening in the west pacific warm pool region and eastern Atlantic region. For SCSMEX, however, the effects of large-scale moistening predominate. Net radiation and sensible and latent hc,it fluxes play a much more important role in the central USA.

Attribution of Extreme Rainfall Events in the South of France Using EURO-CORDEX Simulations

NASA Astrophysics Data System (ADS)

Luu, L. N.; Vautard, R.; Yiou, P.

2017-12-01

The Mediterranean region regularly undergoes episodes of intense precipitation in the fall season that exceed 300mm a day. This study focuses on the role of climate change on the dynamics of the events that occur in the South of France. We used an ensemble of 10 EURO-CORDEX model simulations with two horizontal resolutions (EUR-11: 0.11° and EUR-44: 0.44°) for the attribution of extreme rainfall in the fall in the Cevennes mountain range (South of France). The biases of the simulations were corrected with simple scaling adjustment and a quantile correction (CDFt). This produces five datasets including EUR-44 and EUR-11 with and without scaling adjustment and CDFt-EUR-11, on which we test the impact of resolution and bias correction on the extremes. Those datasets, after pooling all of models together, are fitted by a stationary Generalized Extreme Value distribution for several periods to estimate a climate change signal in the tail of distribution of extreme rainfall in the Cévenne region. Those changes are then interpreted by a scaling model that links extreme rainfall with mean and maximum daily temperature. The results show that higher-resolution simulations with bias adjustment provide a robust and confident increase of intensity and likelihood of occurrence of autumn extreme rainfall in the area in current climate in comparison with historical climate. The probability (exceedance probability) of 1-in-1000-year event in historical climate may increase by a factor of 1.8 under current climate with a confident interval of 0.4 to 5.3 following the CDFt bias-adjusted EUR-11. The change of magnitude appears to follow the Clausius-Clapeyron relation that indicates a 7% increase in rainfall per 1oC increase in temperature.

High Severity Wildfire Effect On Rainfall Infiltration And Runoff: A Cellular Automata Based Simulation

NASA Astrophysics Data System (ADS)

Vergara-Blanco, J. E.; Leboeuf-Pasquier, J.; Benavides-Solorio, J. D. D.

2017-12-01

A simulation software that reproduces rainfall infiltration and runoff for a storm event in a particular forest area is presented. A cellular automaton is utilized to represent space and time. On the time scale, the simulation is composed by a sequence of discrete time steps. On the space scale, the simulation is composed of forest surface cells. The software takes into consideration rain intensity and length, individual forest cell soil absorption capacity evolution, and surface angle of inclination. The software is developed with the C++ programming language. The simulation is executed on a 100 ha area within La Primavera Forest in Jalisco, Mexico. Real soil texture for unburned terrain and high severity wildfire affected terrain is employed to recreate the specific infiltration profile. Historical rainfall data of a 92 minute event is used. The Horton infiltration equation is utilized for infiltration capacity calculation. A Digital Elevation Model (DEM) is employed to reproduce the surface topography. The DEM is displayed with a 3D mesh graph where individual surface cells can be observed. The plot colouring renders water content development at the cell level throughout the storm event. The simulation shows that the cumulative infiltration and runoff which take place at the surface cell level depend on the specific storm intensity, fluctuation and length, overall terrain topography, cell slope, and soil texture. Rainfall cumulative infiltration for unburned and high severity wildfire terrain are compared: unburned terrain exhibits a significantly higher amount of rainfall infiltration.It is concluded that a cellular automaton can be utilized with a C++ program to reproduce rainfall infiltration and runoff under diverse soil texture, topographic and rainfall conditions in a forest setting. This simulation is geared for an optimization program to pinpoint the locations of a series of forest land remediation efforts to support reforestation or to minimize runoff.

Role of monsoon intraseasonal oscillation and its interannual variability in simulation of seasonal mean in CFSv2

NASA Astrophysics Data System (ADS)

Pillai, Prasanth A.; Aher, Vaishali R.

2018-01-01

Intraseasonal oscillation (ISO), which appears as "active" and "break" spells of rainfall, is an important component of Indian summer monsoon (ISM). The present study investigates the potential of new National Centre for Environmental Prediction (NCEP) climate forecast system version 2 (CFSv2) in simulating the ISO with emphasis to its interannual variability (IAV) and its possible role in the seasonal mean rainfall. The present analysis shows that the spatial distribution of CFSv2 rainfall has noticeable differences with observations in both ISO and IAV time scales. Active-break cycle of CFSv2 has similar evolution during both strong and weak years. Regardless of a reasonable El Niño Southern Oscillation (ENSO)-monsoon teleconnection in the model, the overestimated Arabian Sea (AS) sea surface temperature (SST)-convection relationship hinters the large-scale influence of ENSO over the ISM region and adjacent oceans. The ISO scale convections over AS and Bay of Bengal (BoB) have noteworthy contribution to the seasonal mean rainfall, opposing the influence of boundary forcing in these areas. At the same time, overwhelming contribution of ISO component over AS towards the seasonal mean modifies the effect of slow varying boundary forcing to large-scale summer monsoon. The results here underline that, along with the correct simulation of monsoon ISO, its IAV and relationship with the boundary forcing also need to be well captured in coupled models for the accurate simulation of seasonal mean anomalies of the monsoon and its teleconnections.

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Reduced-complexity multi-site rainfall generation: one million years over night using the model TripleM

NASA Astrophysics Data System (ADS)

Breinl, Korbinian; Di Baldassarre, Giuliano; Girons Lopez, Marc

2017-04-01

We assess uncertainties of multi-site rainfall generation across spatial scales and different climatic conditions. Many research subjects in earth sciences such as floods, droughts or water balance simulations require the generation of long rainfall time series. In large study areas the simulation at multiple sites becomes indispensable to account for the spatial rainfall variability, but becomes more complex compared to a single site due to the intermittent nature of rainfall. Weather generators can be used for extrapolating rainfall time series, and various models have been presented in the literature. Even though the large majority of multi-site rainfall generators is based on similar methods, such as resampling techniques or Markovian processes, they often become too complex. We think that this complexity has been a limit for the application of such tools. Furthermore, the majority of multi-site rainfall generators found in the literature are either not publicly available or intended for being applied at small geographical scales, often only in temperate climates. Here we present a revised, and now publicly available, version of a multi-site rainfall generation code first applied in 2014 in Austria and France, which we call TripleM (Multisite Markov Model). We test this fast and robust code with daily rainfall observations from the United States, in a subtropical, tropical and temperate climate, using rain gauge networks with a maximum site distance above 1,000km, thereby generating one million years of synthetic time series. The modelling of these one million years takes one night on a recent desktop computer. In this research, we first start the simulations with a small station network of three sites and progressively increase the number of sites and the spatial extent, and analyze the changing uncertainties for multiple statistical metrics such as dry and wet spells, rainfall autocorrelation, lagged cross correlations and the inter-annual rainfall variability. Our study contributes to the scientific community of earth sciences and the ongoing debate on extreme precipitation in a changing climate by making a stable, and very easily applicable, multi-site rainfall generation code available to the research community and providing a better understanding of the performance of multi-site rainfall generation depending on spatial scales and climatic conditions.

Infiltration and Runoff Measurements on Steep Burned Hillslopes Using a Rainfall Simulator with Variable Rain Intensities

USGS Publications Warehouse

Kinner, David A.; Moody, John A.

2008-01-01

Multiple rainfall intensities were used in rainfall-simulation experiments designed to investigate the infiltration and runoff from 1-square-meter plots on burned hillslopes covered by an ash layer of varying thickness. The 1-square-meter plots were on north- and south-facing hillslopes in an area burned by the Overland fire northwest of Boulder near Jamestown on the Front Range of Colorado. A single-nozzle, wide-angle, multi-intensity rain simulator was developed to investigate the infiltration and runoff on steep (30- to 40-percent gradient) burned hillslopes covered with ash. The simulated rainfall was evaluated for spatial variability, drop size, and kinetic energy. Fourteen rainfall simulations, at three intensities (about 20 millimeters per hour [mm/h], 35 mm/h, and 50 mm/h), were conducted on four plots. Measurements during and after the simulations included runoff, rainfall, suspended-sediment concentrations, surface ash layer thickness, soil moisture, soil grain size, soil lost on ignition, and plot topography. Runoff discharge reached a steady state within 7 to 26 minutes. Steady infiltration rates with the 50-mm/h application rainfall intensity approached 20?35 mm/h. If these rates are projected to rainfall application intensities used in many studies of burned area runoff production (about 80 mm/h), the steady discharge rates are on the lower end of measurements from other studies. Experiments using multiple rainfall intensities (three) suggest that runoff begins at rainfall intensities around 20 mm/h at the 1-square-meter scale, an observation consistent with a 10-mm/h rainfall intensity threshold needed for runoff initiation that has been reported in the literature.

Convective Systems over the South China Sea: Cloud-Resolving Model Simulations.

NASA Astrophysics Data System (ADS)

Tao, W.-K.; Shie, C.-L.; Simpson, J.; Braun, S.; Johnson, R. H.; Ciesielski, P. E.

2003-12-01

The two-dimensional version of the Goddard Cumulus Ensemble (GCE) model is used to simulate two South China Sea Monsoon Experiment (SCSMEX) convective periods [18 26 May (prior to and during the monsoon onset) and 2 11 June (after the onset of the monsoon) 1998]. Observed large-scale advective tendencies for potential temperature, water vapor mixing ratio, and horizontal momentum are used as the main forcing in governing the GCE model in a semiprognostic manner. The June SCSMEX case has stronger forcing in both temperature and water vapor, stronger low-level vertical shear of the horizontal wind, and larger convective available potential energy (CAPE).The temporal variation of the model-simulated rainfall, time- and domain-averaged heating, and moisture budgets compares well to those diagnostically determined from soundings. However, the model results have a higher temporal variability. The model underestimates the rainfall by 17% to 20% compared to that based on soundings. The GCE model-simulated rainfall for June is in very good agreement with the Tropical Rainfall Measuring Mission (TRMM), precipitation radar (PR), and the Global Precipitation Climatology Project (GPCP). Overall, the model agrees better with observations for the June case rather than the May case.The model-simulated energy budgets indicate that the two largest terms for both cases are net condensation (heating/drying) and imposed large-scale forcing (cooling/moistening). These two terms are opposite in sign, however. The model results also show that there are more latent heat fluxes for the May case. However, more rainfall is simulated for the June case. Net radiation (solar heating and longwave cooling) are about 34% and 25%, respectively, of the net condensation (condensation minus evaporation) for the May and June cases. Sensible heat fluxes do not contribute to rainfall in either of the SCSMEX cases. Two types of organized convective systems, unicell (May case) and multicell (June case), are simulated by the model. They are determined by the observed mean U wind shear (unidirectional versus reverse shear profiles above midlevels).Several sensitivity tests are performed to examine the impact of the radiation, microphysics, and large-scale mean horizontal wind on the organization and intensity of the SCSMEX convective systems.

Effect of rainfall simulator and plot scale on overland flow and phosphorus transport.

PubMed

Sharpley, Andrew; Kleinman, Peter

2003-01-01

Rainfall simulation experiments are widely used to study erosion and contaminant transport in overland flow. We investigated the use of two rainfall simulators designed to rain on 2-m-long (2-m2) and 10.7-m-long (32.6-m2) plots to estimate overland flow and phosphorus (P) transport in comparison with watershed-scale data. Simulated rainfall (75 mm h(-1)) generated more overland flow from 2-m-long (20 L m2) than from 10.7-m-long (10 L m2) plots established in grass, no-till corn (Zea mays L.), and recently tilled fields, because a relatively greater area of the smaller plots became saturated (>75% of area) during rainfall compared with large plots (<75% area). Although average concentrations of dissolved reactive phosphorus (DRP) in overland flow were greater from 2-m-long (0.50 mg L(-1)) than 10.7-m-long (0.35 mg L(-1)) plots, the relationship between DRP and Mehlich-3 soil P (as defined by regression slope) was similar for both plots and for published watershed data (0.0022 for grassed, 0.0036 for no-till, and 0.0112 for tilled sites). Conversely, sediment, particulate phosphorus (PP), and total phosphorus (TP) concentrations and selective transport of soil fines (<2 microm) were significantly lower from 2- than 10.7-m-long plots. However, slopes of the logarithmic regression between P enrichment ratio and sediment discharge were similar (0.281-0.301) for 2- and 10.7-m-long plots, and published watershed data. While concentrations and loads of P change with plot scales, processes governing DRP and PP transport in overland flow are consistent, supporting the limited use of small plots and rainfall simulators to assess the relationship between soil P and overland flow P as a function of soil type and management.

Meteorological impact assessment of possible large scale irrigation in Southwest Saudi Arabia

NASA Astrophysics Data System (ADS)

Ter Maat, H. W.; Hutjes, R. W. A.; Ohba, R.; Ueda, H.; Bisselink, B.; Bauer, T.

2006-11-01

On continental to regional scales feedbacks between landuse and landcover change and climate have been widely documented over the past 10-15 years. In the present study we explore the possibility that also vegetation changes over much smaller areas may affect local precipitation regimes. Large scale (˜ 10 5 ha) irrigated plantations in semi-arid environments under particular conditions may affect local circulations and induce additional rainfall. Capturing this rainfall 'surplus' could then reduce the need for external irrigation sources and eventually lead to self-sustained water cycling. This concept is studied in the coastal plains in South West Saudi Arabia where the mountains of the Asir region exhibit the highest rainfall of the peninsula due to orographic lifting and condensation of moisture imported with the Indian Ocean monsoon and with disturbances from the Mediterranean Sea. We use a regional atmospheric modeling system (RAMS) forced by ECMWF analysis data to resolve the effect of complex surface conditions in high resolution (Δ x = 4 km). After validation, these simulations are analysed with a focus on the role of local processes (sea breezes, orographic lifting and the formation of fog in the coastal mountains) in generating rainfall, and on how these will be affected by large scale irrigated plantations in the coastal desert. The validation showed that the model simulates the regional and local weather reasonably well. The simulations exhibit a slightly larger diurnal temperature range than those captured by the observations, but seem to capture daily sea-breeze phenomena well. Monthly rainfall is well reproduced at coarse resolutions, but appears more localized at high resolutions. The hypothetical irrigated plantation (3.25 10 5 ha) has significant effects on atmospheric moisture, but due to weakened sea breezes this leads to limited increases of rainfall. In terms of recycling of irrigation gifts the rainfall enhancement in this particular setting is rather insignificant.

The Impact of Simulated Mesoscale Convective Systems on Global Precipitation: A Multiscale Modeling Study

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, Jiun-Dar

2017-01-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multi-scale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. In this study, the impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE) model and Goddard MMF (GMMF). The results indicate that both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the GMMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feed back are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.

Rainfall and Extratropical Transition of Tropical Cyclones: Simulation, Prediction, and Projection

NASA Astrophysics Data System (ADS)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET events on the projected increase of TC frequency in the eastern North Atlantic, highlighting increased exposure of the northeastern United States and Western Europe to storm hazards. Retrospective seasonal forecast experiments demonstrate the skill of HiFLOR in predicting basinwide and regional ET frequency. This skill, however, is not seen in the seasonal prediction of ET rate. More work on the property of signal-to-noise ratio of ET rate is needed.

A sensitivity study of the coupled simulation of the Northeast Brazil rainfall variability

NASA Astrophysics Data System (ADS)

Misra, Vasubandhu

2007-06-01

Two long-term coupled ocean-land-atmosphere simulations with slightly different parameterization of the diagnostic shallow inversion clouds in the atmospheric general circulation model (AGCM) of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled climate model are compared for their annual cycle and interannual variability of the northeast Brazil (NEB) rainfall variability. It is seen that the solar insolation affected by the changes to the shallow inversion clouds results in large scale changes to the gradients of the SST and the surface pressure. The latter in turn modulates the surface convergence and the associated Atlantic ITCZ precipitation and the NEB annual rainfall variability. In contrast, the differences in the NEB interannual rainfall variability between the two coupled simulations is attributed to their different remote ENSO forcing.

Simulation of localized heavy precipitation in South Korea on 20 June 2014: sensitivity test of integration time-step size and an effect of topographic resolution using WRF model

NASA Astrophysics Data System (ADS)

Roh, Joon-Woo; Jee, Joon-Bum; Lim, A.-Young; Choi, Young-Jean

2015-04-01

Korean warm-season rainfall, accounting for about three-fourths of the annual precipitation, is primarily caused by Changma front, which is a kind of the East Asian summer monsoon, and localized heavy rainfall with convective instability. Various physical mechanisms potentially exert influences on heavy precipitation over South Korea. Representatively, the middle latitude and subtropical weather fronts, associated with a quasi-stationary moisture convergence zone among varying air masses, make up one of the main rain-bearing synoptic scale systems. Localized heavy rainfall events in South Korea generally arise from mesoscale convective systems embedded in these synoptic scale disturbances along the Changma front or convective instabilities resulted from unstable air mass including the direct or indirect effect of typhoons. In recent years, torrential rainfalls, which are more than 30mm/hour of precipitation amount, in warm-season has increased threefold in Seoul, which is a metropolitan city in South Korea. In order to investigate multiple potential causes of warm-season localized heavy precipitation in South Korea, a localized heavy precipitation case took place on 20 June 2014 at Seoul. This case was mainly seen to be caused by short-wave trough, which is associated with baroclinic instability in the northwest of Korea, and a thermal low, which has high moist and warm air through analysis. This structure showed convective scale torrential rain was embedded in the dynamic and in the thermodynamic structures. In addition to, a sensitivity of rainfall amount and maximum rainfall location to the integration time-step sizes was investigated in the simulations of a localized heavy precipitation case using Weather Research and Forecasting model. The simulation of time-step sizes of 9-27s corresponding to a horizontal resolution of 4.5km and 1.5km varied slightly difference of the maximum rainfall amount. However, the sensitivity of spatial patterns and temporal variations in rainfall were relatively small for the time-step sizes. The effect of topography was also important in the localized heavy precipitation simulation.

Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations

NASA Astrophysics Data System (ADS)

Zhou, Y.; Tao, W.; Hou, A. Y.; Zeng, X.; Shie, C.

2007-12-01

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model for different environmental conditions, i.e., the South China Sea Monsoon Experiment (SCSMEX), CRYSTAL-FACE, and KAWJEX are compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and as well as cloud observations from the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. The model presents large discrepancies in rain spectrum and vertical hydrometer profiles. The discrepancy in the precipitation field is also consistent with the cloud and radiation observations. The study will focus on the effects of large scale forcing and microphysics to the simulated model- observation discrepancies.

An assessment of the feasibility of the use of satellite-only rainfall estimates for the hydrological monitoring in central Italy

NASA Astrophysics Data System (ADS)

Campo, Lorenzo; Caparrini, Francesca

2013-04-01

The need for accurate distributed hydrological modelling has constantly increased in last years for several purposes: agricultural applications, water resources management, hydrological balance at watershed scale, floods forecast. The main input for the hydrological numerical models is rainfall data that present, at the same time, a large availability of measures (in gauged regions, with respect to other micro-meteorological variables) and the most complex spatial patterns. While also in presence of densely gauged watersheds the spatial interpolation of the rainfall is a non-trivial problem, due to the spatial intermittence of the variable (especially at finer temporal scales), ungauged regions need an alternative source of rainfall data in order to perform the hydrological modelling. Such source can be constituted by the satellite-estimated rainfall fields, with reference to both geostationary and polar-orbit platforms. In this work the rainfall product obtained by the Aqua-AIRS sensor were used in order to assess the feasibility of the use of satellite-based rainfall as input for distributed hydrological modelling. The MOBIDIC (MOdello di BIlancio Distribuito e Continuo) model, developed at the Department of civil and Environmental Engineering of the University of Florence and operationally used by Tuscany Region and Umbria Region for flood prediction and management, was used for the experiments. In particular three experiments were carried on: a) hydrological simulation with the use of rain-gauges data, b) simulation with the use of satellite-only rainfall estimates, c) simulation with the combined use of the two sources of data in order to obtain an optimal estimate of the actual rainfall fields. The domain of the study was the central Italy. Several critical events occurred in the area were analyzed. A discussion of the results is provided.

Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

NASA Astrophysics Data System (ADS)

Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

2017-10-01

In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041-2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041-2060) compared to the base period (1961-2000).

How is overland flow produced under intermittent rain? An analysis using plot-scale rainfall simulation on dryland soils

NASA Astrophysics Data System (ADS)

Dunkerley, David

2018-01-01

The characteristic intermittency of rainfall includes temporary cessations (hiatuses), as well as periods of very low intensity within more intense events. To understand how these characteristics of rainfall affect overland flow production, rainfall simulations involving repeated cycles of on-off intermittency were carried out on dryland soils in arid western New South Wales, Australia. Periods of rain (10 mm/h) and no-rain were applied in alternation with cycle times from 3 min to 25 min, in experiments lasting 1-1.5 h. Results showed that intermittency could delay the onset of runoff by more than 30 min, reduce the runoff ratio, reduce the peak runoff rate, and reduce the apparent event infiltration rate by 30-45%. When hiatuses in rainfall were longer than 15-20 min, runoff that had resulted from prior rain ceased completely before the recommencement of rain. Results demonstrate that if rainfall intermittency is not accounted for, estimates of infiltrability based on runoff plot data can be systematically in error. Despite the use of intermittent rain, the episodic occurrence of runoff could be predicted successfully by fitting multiple affine Horton infiltration equations, whose changing f0 and Kf coefficients, but uniform values of fc, reflected the redistribution of soil moisture and the change in the infiltrability f during hiatuses in rainfall. The value of fc varied little among the fitted equations, so constituting an affine set of relationships. This new approach provides an alternative to the use of steady-state methods that are common in rainfall simulation experiments and which typically yield only an estimate of fc. The new field results confirm that intermittency affects infiltration and runoff depths and timing at plot scale and on intra-event timescales. Additional work on other soil types, and at other spatial and temporal scales, is needed to test the generality of these findings.

Constraining continuous rainfall simulations for derived design flood estimation

NASA Astrophysics Data System (ADS)

Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.

2016-11-01

Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

The development of a capability for aerodynamic testing of large-scale wing sections in a simulated natural rain environment

NASA Technical Reports Server (NTRS)

Bezos, Gaudy M.; Cambell, Bryan A.; Melson, W. Edward

1989-01-01

A research technique to obtain large-scale aerodynamic data in a simulated natural rain environment has been developed. A 10-ft chord NACA 64-210 wing section wing section equipped with leading-edge and trailing-edge high-lift devices was tested as part of a program to determine the effect of highly-concentrated, short-duration rainfall on airplane performance. Preliminary dry aerodynamic data are presented for the high-lift configuration at a velocity of 100 knots and an angle of attack of 18 deg. Also, data are presented on rainfield uniformity and rainfall concentration intensity levels obtained during the calibration of the rain simulation system.

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

The impact of mesoscale convective systems on global precipitation: A modeling study

NASA Astrophysics Data System (ADS)

Tao, Wei-Kuo

2017-04-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. Typical MCSs have horizontal scales of a few hundred kilometers (km); therefore, a large domain and high resolution are required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multi-scale modeling frameworks (MMFs) with 32 CRM grid points and 4 km grid spacing also might not have sufficient resolution and domain size for realistically simulating MCSs. In this study, the impact of MCSs on precipitation processes is examined by conducting numerical model simulations using the Goddard Cumulus Ensemble model (GCE) and Goddard MMF (GMMF). The results indicate that both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with less grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show that the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are either weaker or reduced in the GMMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feed back are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures (SSTs) is conducted and results in both reduced surface rainfall and evaporation.

High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2016-04-01

Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

Scaling laws for testing of high lift airfoils under heavy rainfall

NASA Technical Reports Server (NTRS)

Bilanin, A. J.

1985-01-01

The results of studies regarding the effect of rainfall about aircraft are briefly reviewed. It is found that performance penalties on airfoils have been identified in subscale tests. For this reason, it is of great importance that scaling laws be dveloped to aid in the extrapolation of these data to fullscale. The present investigation represents an attempt to develop scaling laws for testing subscale airfoils under heavy rain conditions. Attention is given to rain statistics, airfoil operation in heavy rain, scaling laws, thermodynamics of condensation and/or evaporation, rainfall and airfoil scaling, aspects of splash back, film thickness, rivulets, and flap slot blockage. It is concluded that the extrapolation of airfoil performance data taken at subscale under simulated heavy rain conditions to fullscale must be undertaken with caution.

Organization of vertical shear of wind and daily variability of monsoon rainfall

NASA Astrophysics Data System (ADS)

Gouda, K. C.; Goswami, P.

2016-10-01

Very little is known about the mechanisms that govern the day to day variability of the Indian summer monsoon (ISM) rainfall; in the current dominant view, the daily rainfall is essentially a result of chaotic dynamics. Most studies in the past have thus considered monsoon in terms of its seasonal (June-September) or monthly rainfall. We show here that the daily rainfall in June is associated with vertical shear of horizontal winds at specific scales. While vertical shear had been used in the past to investigate interannual variability of seasonal rainfall, rarely any effort has been made to examine daily rainfall. Our work shows that, at least during June, the daily rainfall variability of ISM rainfall is associated with a large scale dynamical coherence in the sense that the vertical shear averaged over large spatial extents are significantly correlated with area-averaged daily rainfall. An important finding from our work is the existence of a clearly delineated monsoon shear domain (MSD) with strong coherence between area-averaged shear and area-averaged daily rainfall in June; this association of daily rainfall is not significant with shear over only MSD. Another important feature is that the association between daily rainfall and vertical shear is present only during the month of June. Thus while ISM (June-September) is a single seasonal system, it is important to consider the dynamics and variation of June independently of the seasonal ISM rainfall. The association between large-scale organization of circulation and daily rainfall is suggested as a basis for attempting prediction of daily rainfall by ensuring accurate simulation of wind shear.

Spatial and temporal variability in the R-5 infiltration data set: Déjà vu and rainfall-runoff simulations

NASA Astrophysics Data System (ADS)

Loague, Keith; Kyriakidis, Phaedon C.

1997-12-01

This paper is a continuation of the event-based rainfall-runoff model evaluation study reported by Loague and Freeze [1985[. Here we reevaluate the performance of a quasi-physically based rainfall-runoff model for three large events from the well-known R-5 catchment. Five different statistical criteria are used to quantitatively judge model performance. Temporal variability in the large R-5 infiltration data set [Loague and Gander, 1990] is filtered by working in terms of permeability. The transformed data set is reanalyzed via geostatistical methods to model the spatial distribution of permeability across the R-5 catchment. We present new estimates of the spatial distribution of infiltration that are in turn used in our rainfall-runoff simulations with the Horton rainfall-runoff model. The new rainfall-runoff simulations, complicated by reinfiltration impacts at the smaller scales of characterization, indicate that the near-surface hydrologic response of the R-5 catchment is most probably dominated by a combination of the Horton and Dunne overland flow mechanisms.

The capacity of radar, crowdsourced personal weather stations and commercial microwave links to monitor small scale urban rainfall

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; de Vos, L. W.; Leijnse, H.; Overeem, A.; Raupach, T. H.; Berne, A.

2017-12-01

For the purpose of urban rainfall monitoring high resolution rainfall measurements are desirable. Typically C-band radar can provide rainfall intensities at km grid cells every 5 minutes. Opportunistic sensing with commercial microwave links yields rainfall intensities over link paths within cities. Additionally, recent developments have made it possible to obtain large amounts of urban in situ measurements from weather amateurs in near real-time. With a known high resolution simulated rainfall event the accuracy of these three techniques is evaluated, taking into account their respective existing layouts and sampling methods. Under ideal measurement conditions, the weather station networks proves to be most promising. For accurate estimation with radar, an appropriate choice for Z-R relationship is vital. Though both the microwave links and the weather station networks are quite dense, both techniques will underestimate rainfall if not at least one link path / station captures the high intensity rainfall peak. The accuracy of each technique improves when considering rainfall at larger scales, especially by increasing time intervals, with the steepest improvements found in microwave links.

SIMULATED IMPACTS OF SMALL-SCALE SPATIAL DISTRIBUTION OF IMPERVIOUS AREA ON RUNOFF RESPONSE OF FIELD-SCALE CATCHMENTS

EPA Science Inventory

Impervious surface is known to negatively affect catchment hydrology through both its extent and spatial distribution. In this study, we empirically quantify via model simulations the impacts of different configurations of impervious surface on watershed response to rainfall. An ...

Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.

1990-01-01

Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.

Precipitation Processes Derived from TRMM Satellite Data, Cloud Resolving Model and Field Campaigns

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid. and solid water. Present large-scale weather and climate models can simulate cloud latent heat release only crudely thus reducing their confidence in predictions on both global and regional scales. In this paper, NASA Tropical Rainfall Measuring (TRMM) precipitation radar (PR) derived rainfall information and the Goddard Convective and Stratiform Heating (CSH) algorithm used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to October 2000. Rainfall latent heating and radar reflectively structure between ENSO (1997-1998 winter) and non-ENSO (1998-1999 winter) periods are examined and compared. The seasonal variation of heating over various geographic locations (i.e. Indian ocean vs west Pacific; Africa vs S. America) are also analyzed. In addition, the relationship between rainfall latent heating maximum heating level), radar reflectively and SST are examined.

Characteristics of Heavy Summer Rainfall in Southwestern Taiwan in Relation to Orographic Effects

NASA Technical Reports Server (NTRS)

Chen, Ching-Sen; Chen, Wan-Chin; Tao, Wei-Kuo

2004-01-01

On the windward side of southwestern Taiwan, about a quarter to a half of all rainfall during mid-July through August from 1994 to 2000 came from convective systems embedded in the southwesterly monsoon flow. k this study, the causes of two heavy rainfall events (daily rainfall exceeding 100 mm day over at least three rainfall stations) observed over the slopes and/or lowlands of southwestern Taiwan were examined. Data from European Center for Medium-Range Weather Forecasts /Tropical Ocean- Global Atmosphere (EC/TOGA) analyses, the rainfall stations of the Automatic Rainfall and Meteorological Telemetry System (ARMTS) and the conventional surface stations over Taiwan, and the simulation results from a regional-scale numerical model were used to accomplish the objectives. In one event (393 mm day on 9 August 1999), heavy rainfall was observed over the windward slopes of southern Taiwan in a potentially unstable environment with very humid air around 850 hPa. The extreme accumulation was simulated and attributed to orographic lifting effects. No preexisting convection drifted in from the Taiwan Strait into western Taiwan.

Rainfall-runoff simulation in urban hydology - An indoor physical model

NASA Astrophysics Data System (ADS)

Isidoro, Jorge; Silveira, Alexandre; da Silva, António; Gonçalves, Flávio; de Deus, Fábio; dos Reis, Simone

2015-04-01

According to the UN the current levels of urbanization are unprecedented and so is the number and size of the world's largest cities. Moreover, in the next four decades, all of the world's population growth is most likely to take place in urban areas. This growth will include a draw in some of the rural population through rural to urban migration. The increase in size of individual concentrations of people (e.g., cities) is a consequence of the urbanization process that has an important role on the rainfall-runoff process. This reality implies more attention to the study of urban flooding, among other natural hazards. This work aims to present a laboratory (indoor) physical model at a 1:100 scale of an urban area under simulated rainfall (pressurized nozzles). The model, a V-shaped rectangular area (2.00m × 4.00m) with the ability to adjust its longitudinal and transversal slopes, allows placing blocks simulating several geometries of buildings. This model was conceived and developed at the Institute of Science and Technology of the Federal University of Alfenas (MG) in Brazil, where it is used for research and teaching activities. Several experiments were completed in order to simulate the rainfall-runoff process over an impervious area with and without buildings, with distinct longitudinal and transversal slopes. Significant differences were found in the shape of the resulting hydrographs. This work will allow assessing the possibility of scaling the results obtained with this indoor model to a larger-scale (1:25 to 1:10) outdoor model which is currently being designed.

Soil erosion predictions from a landscape evolution model - An assessment of a post-mining landform using spatial climate change analogues.

PubMed

Hancock, G R; Verdon-Kidd, D; Lowry, J B C

2017-12-01

Landscape Evolution Modelling (LEM) technologies provide a means by which it is possible to simulate the long-term geomorphic stability of a conceptual rehabilitated landform. However, simulations rarely consider the potential effects of anthropogenic climate change and consequently risk not accounting for the range of rainfall variability that might be expected in both the near and far future. One issue is that high resolution (both spatial and temporal) rainfall projections incorporating the potential effects of greenhouse forcing are required as input. However, projections of rainfall change are still highly uncertain for many regions, particularly at sub annual/seasonal scales. This is the case for northern Australia, where a decrease or an increase in rainfall post 2030 is considered equally likely based on climate model simulations. The aim of this study is therefore to investigate a spatial analogue approach to develop point scale hourly rainfall scenarios to be used as input to the CAESAR - Lisflood LEM to test the sensitivity of the geomorphic stability of a conceptual rehabilitated landform to potential changes in climate. Importantly, the scenarios incorporate the range of projected potential increase/decrease in rainfall for northern Australia and capture the expected envelope of erosion rates and erosion patterns (i.e. where erosion and deposition occurs) over a 100year modelled period. We show that all rainfall scenarios produce sediment output and gullying greater than that of the surrounding natural system, however a 'wetter' future climate produces the highest output. Importantly, incorporating analogue rainfall scenarios into LEM has the capacity to both improve landform design and enhance the modelling software. Further, the method can be easily transferred to other sites (both nationally and internationally) where rainfall variability is significant and climate change impacts are uncertain. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Modelling of Sub-daily Hydrological Processes Using Daily Time-Step Models: A Distribution Function Approach to Temporal Scaling

NASA Astrophysics Data System (ADS)

Kandel, D. D.; Western, A. W.; Grayson, R. B.

2004-12-01

Mismatches in scale between the fundamental processes, the model and supporting data are a major limitation in hydrologic modelling. Surface runoff generation via infiltration excess and the process of soil erosion are fundamentally short time-scale phenomena and their average behaviour is mostly determined by the short time-scale peak intensities of rainfall. Ideally, these processes should be simulated using time-steps of the order of minutes to appropriately resolve the effect of rainfall intensity variations. However, sub-daily data support is often inadequate and the processes are usually simulated by calibrating daily (or even coarser) time-step models. Generally process descriptions are not modified but rather effective parameter values are used to account for the effect of temporal lumping, assuming that the effect of the scale mismatch can be counterbalanced by tuning the parameter values at the model time-step of interest. Often this results in parameter values that are difficult to interpret physically. A similar approach is often taken spatially. This is problematic as these processes generally operate or interact non-linearly. This indicates a need for better techniques to simulate sub-daily processes using daily time-step models while still using widely available daily information. A new method applicable to many rainfall-runoff-erosion models is presented. The method is based on temporal scaling using statistical distributions of rainfall intensity to represent sub-daily intensity variations in a daily time-step model. This allows the effect of short time-scale nonlinear processes to be captured while modelling at a daily time-step, which is often attractive due to the wide availability of daily forcing data. The approach relies on characterising the rainfall intensity variation within a day using a cumulative distribution function (cdf). This cdf is then modified by various linear and nonlinear processes typically represented in hydrological and erosion models. The statistical description of sub-daily variability is thus propagated through the model, allowing the effects of variability to be captured in the simulations. This results in cdfs of various fluxes, the integration of which over a day gives respective daily totals. Using 42-plot-years of surface runoff and soil erosion data from field studies in different environments from Australia and Nepal, simulation results from this cdf approach are compared with the sub-hourly (2-minute for Nepal and 6-minute for Australia) and daily models having similar process descriptions. Significant improvements in the simulation of surface runoff and erosion are achieved, compared with a daily model that uses average daily rainfall intensities. The cdf model compares well with a sub-hourly time-step model. This suggests that the approach captures the important effects of sub-daily variability while utilizing commonly available daily information. It is also found that the model parameters are more robustly defined using the cdf approach compared with the effective values obtained at the daily scale. This suggests that the cdf approach may offer improved model transferability spatially (to other areas) and temporally (to other periods).

Use NU-WRF and GCE Model to Simulate the Precipitation Processes During MC3E Campaign

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Wu, Di; Matsui, Toshi; Li, Xiaowen; Zeng, Xiping; Peter-Lidard, Christa; Hou, Arthur

2012-01-01

One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

2017-12-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic precipitation, fed into a rainfall-runoff model to derive the flood frequency in the Tirolean Alps in Austria. Given the number of generated events, the simulation framework is able to generate a large variety of rainfall patterns, as well as reproduce the variograms of relevant extreme rainfall events in the region of interest.

Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

NASA Astrophysics Data System (ADS)

Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka

2016-04-01

Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our hierarchical MC model with the semi-parametric model in preserving rainfall variability in daily, monthly, and multi-year scales. To calibrate the parameters of both models and assess their ability to preserve observed statistics, we have used ground based data from 15 raingauge stations around Australia, which consist a wide range of climate zones including coastal, monsoonal, and arid climate characteristics. In preliminary results, both models show comparative performances in preserving the multi-year variability of rainfall depth and occurrence. However, the semi-parametric model shows a tendency of overestimating the mean rainfall depth, while our model shows a tendency of overestimating the number of wet days. We will discuss further the relative merits of the both models for hydrology simulation in the presentation.

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations

PubMed Central

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998–2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002–2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability. PMID:27010692

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations.

PubMed

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998-2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002-2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability.

Rainfall Across the Globe: Precipitation. The Role of Landmass in Monsoon Development. The Relationship Between Precipitation and Sea Surface Temperature on Decadal Time Scales

NASA Technical Reports Server (NTRS)

Chao, Winston; Schubert, Siegfried; Suarez, Max; Pegion, Philip

2000-01-01

The numerical simulation of precipitation helps scientists understand the complex mechanisms that determine how and why rainfall is distributed across the globe. Simulation aids in the development of forecastin,g efforts that inform policies regarding the management of water resources. Precipitation modeling also provides short-term warnings, for emergencies such as flash floods and mudslides. Just as precipitation modeling can warn of an impending abundance of rainfall, it can help anticipate the absence of rainfall in drought. What constitutes a drought? A meteorological drought simply means that an area is getting a significantly lower amount of rain than usual over a prolonged period of time and an agricultural drought is based on the level of soil moisture.

Planting Patterns and Deficit Irrigation Strategies to Improve Wheat Production and Water Use Efficiency under Simulated Rainfall Conditions

PubMed Central

Ali, Shahzad; Xu, Yueyue; Ma, Xiangcheng; Ahmad, Irshad; Kamran, Muhammad; Dong, Zhaoyun; Cai, Tie; Jia, Qianmin; Ren, Xiaolong; Zhang, Peng; Jia, Zhikuan

2017-01-01

The ridge furrow (RF) rainwater harvesting system is an efficient way to enhance rainwater accessibility for crops and increase winter wheat productivity in semi-arid regions. However, the RF system has not been promoted widely in the semi-arid regions, which primarily exist in remote hilly areas. To exploit its efficiency on a large-scale, the RF system needs to be tested at different amounts of simulated precipitation combined with deficit irrigation. Therefore, in during the 2015–16 and 2016–17 winter wheat growing seasons, we examined the effects of two planting patterns: (1) the RF system and (2) traditional flat planting (TF) with three deficit irrigation levels (150, 75, 0 mm) under three simulated rainfall intensity (1: 275, 2: 200, 3: 125 mm), and determined soil water storage profile, evapotranspiration rate, grain filling rate, biomass, grain yield, and net economic return. Over the two study years, the RF treatment with 200 mm simulated rainfall and 150 mm deficit irrigation (RF2150) significantly (P < 0.05) increased soil water storage in the depth of (200 cm); reduced ET at the field scale by 33%; increased total dry matter accumulation per plant; increased the grain-filling rate; and improved biomass (11%) and grain (19%) yields. The RF2150 treatment thus achieved a higher WUE (76%) and RIWP (21%) compared to TF. Grain-filling rates, grain weight of superior and inferior grains, and net economic profit of winter wheat responded positively to simulated rainfall and deficit irrigation under both planting patterns. The 200 mm simulated rainfall amount was more economical than other precipitation amounts, and led to slight increases in soil water storage, total dry matter per plant, and grain yield; there were no significant differences when the simulated rainfall was increased beyond 200 mm. The highest (12,593 Yuan ha−1) net income profit was attained using the RF system at 200 mm rainfall and 150 mm deficit irrigation, which also led to significantly higher grain yield, WUE, and RIWP than all other treatments. Thus, we recommend the RF2150 treatment for higher productivity, income profit, and improve WUE in the dry-land farming system of China. PMID:28878787

The impact of simulated mesoscale convective systems on global precipitation: A multiscale modeling study

NASA Astrophysics Data System (ADS)

Tao, Wei-Kuo; Chern, Jiun-Dar

2017-06-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multiscale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. The impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE, a CRM) model and Goddard MMF that uses the GCEs as its embedded CRMs. Both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the Goddard MMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feedback are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.

Analysis of the sensitivity to rainfall spatio-temporal variability of an operational urban rainfall-runoff model in a multifractal framework

NASA Astrophysics Data System (ADS)

Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

2011-12-01

In large urban areas, storm water management is a challenge with enlarging impervious areas. Many cities have implemented real time control (RTC) of their urban drainage system to either reduce overflow or limit urban contamination. A basic component of RTC is hydraulic/hydrologic model. In this paper we use the multifractal framework to suggest an innovative way to test the sensitivity of such a model to the spatio-temporal variability of its rainfall input. Indeed the rainfall variability is often neglected in urban context, being considered as a non-relevant issue at the scales involve. Our results show that on the contrary the rainfall variability should be taken into account. Universal multifractals (UM) rely on the concept of multiplicative cascade and are a standard tool to analyze and simulate with a reduced number of parameters geophysical processes that are extremely variable over a wide range of scales. This study is conducted on a 3 400 ha urban area located in Seine-Saint-Denis, in the North of Paris (France). We use the operational semi-distributed model that was calibrated by the local authority (Direction Eau et Assainnissement du 93) that is in charge of urban drainage. The rainfall data comes from the C-Band radar of Trappes operated by Météo-France. The rainfall event of February 9th, 2009 was used. A stochastic ensemble approach was implemented to quantify the uncertainty on discharge associated to the rainfall variability occurring at scales smaller than 1 km x 1 km x 5 min that is usually available with C-band radar networks. An analysis of the quantiles of the simulated peak flow showed that the uncertainty exceeds 20 % for upstream links. To evaluate a potential gain from a direct use of the rainfall data available at the resolution of X-band radar, we performed similar analysis of the rainfall fields of the degraded resolution of 9 km x 9 km x 20 min. The results show a clear decrease in uncertainty when the original resolution of C-band radar data is used. This analysis highlights the interest of implementing X-band radars in urban areas. Indeed such radars provide the rainfall data at a hectometric resolution that would enable a better nowcasting and management of storm water. The multifractal properties of the simulated hydrographs were analysed with the help of simulated rainfall fields of resolution 111 m x 111 m x 1 min, lasting 4 hours, and corresponding to a 5 year return period event. On the whole, the discharge exhibits a good scaling behaviour over the range 4 h - 5 min. Both UM parameters tend to be greater for the discharge than for the rainfall. The notion of maximum probable singularity was used to clarify the consequences on the assessment of extremes. It appears that the urban drainage network basically reproduces the extremes, or only slightly damps them, at least in terms of multifractal statistics. The results were obtained with the financial support from the EU FP7 SMARTesT Project and the Chair "Hydrology for Resilient Cities" (sponsored by Veolia) of Ecole des Ponts ParisTech.

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

NASA Astrophysics Data System (ADS)

Martin, Gill M.; Klingaman, Nicholas P.; Moise, Aurel F.

2017-01-01

This study analyses tropical rainfall variability (on a range of temporal and spatial scales) in a set of parallel Met Office Unified Model (MetUM) simulations at a range of horizontal resolutions, which are compared with two satellite-derived rainfall datasets. We focus on the shorter scales, i.e. from the native grid and time step of the model through sub-daily to seasonal, since previous studies have paid relatively little attention to sub-daily rainfall variability and how this feeds through to longer scales. We find that the behaviour of the deep convection parametrization in this model on the native grid and time step is largely independent of the grid-box size and time step length over which it operates. There is also little difference in the rainfall variability on larger/longer spatial/temporal scales. Tropical convection in the model on the native grid/time step is spatially and temporally intermittent, producing very large rainfall amounts interspersed with grid boxes/time steps of little or no rain. In contrast, switching off the deep convection parametrization, albeit at an unrealistic resolution for resolving tropical convection, results in very persistent (for limited periods), but very sporadic, rainfall. In both cases, spatial and temporal averaging smoothes out this intermittency. On the ˜ 100 km scale, for oceanic regions, the spectra of 3-hourly and daily mean rainfall in the configurations with parametrized convection agree fairly well with those from satellite-derived rainfall estimates, while at ˜ 10-day timescales the averages are overestimated, indicating a lack of intra-seasonal variability. Over tropical land the results are more varied, but the model often underestimates the daily mean rainfall (partly as a result of a poor diurnal cycle) but still lacks variability on intra-seasonal timescales. Ultimately, such work will shed light on how uncertainties in modelling small-/short-scale processes relate to uncertainty in climate change projections of rainfall distribution and variability, with a view to reducing such uncertainty through improved modelling of small-/short-scale processes.

Errors and uncertainties in regional climate simulations of rainfall variability over Tunisia: a multi-model and multi-member approach

NASA Astrophysics Data System (ADS)

Fathalli, Bilel; Pohl, Benjamin; Castel, Thierry; Safi, Mohamed Jomâa

2018-02-01

Temporal and spatial variability of rainfall over Tunisia (at 12 km spatial resolution) is analyzed in a multi-year (1992-2011) ten-member ensemble simulation performed using the WRF model, and a sample of regional climate hindcast simulations from Euro-CORDEX. RCM errors and skills are evaluated against a dense network of local rain gauges. Uncertainties arising, on the one hand, from the different model configurations and, on the other hand, from internal variability are furthermore quantified and ranked at different timescales using simple spread metrics. Overall, the WRF simulation shows good skill for simulating spatial patterns of rainfall amounts over Tunisia, marked by strong altitudinal and latitudinal gradients, as well as the rainfall interannual variability, in spite of systematic errors. Mean rainfall biases are wet in both DJF and JJA seasons for the WRF ensemble, while they are dry in winter and wet in summer for most of the used Euro-CORDEX models. The sign of mean annual rainfall biases over Tunisia can also change from one member of the WRF ensemble to another. Skills in regionalizing precipitation over Tunisia are season dependent, with better correlations and weaker biases in winter. Larger inter-member spreads are observed in summer, likely because of (1) an attenuated large-scale control on Mediterranean and Tunisian climate, and (2) a larger contribution of local convective rainfall to the seasonal amounts. Inter-model uncertainties are globally stronger than those attributed to model's internal variability. However, inter-member spreads can be of the same magnitude in summer, emphasizing the important stochastic nature of the summertime rainfall variability over Tunisia.

Do Plot Scale Studies Yield Useful Data When Assessing Field Scale Practices?

USDA-ARS?s Scientific Manuscript database

Plot scale data has been used to develop models used to assess field and watershed scale nutrient losses. The objective of this study was to determine if phosphorus (P) loss results from plot scale rainfall simulation studies are “directionally correct” when compared to field scale P losses. Two fie...

Interannual Tropical Rainfall Variability in General Circulation Model Simulations Associated with the Atmospheric Model Intercomparison Project.

NASA Astrophysics Data System (ADS)

Sperber, K. R.; Palmer, T. N.

1996-11-01

The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall variability was also best reproduced. However, for all regions the skill was less than that of the ECMWF model.The relationships of the all-India and Sahel rainfall/SST teleconnections with horizontal resolution, convection scheme closure, and numerics have been evaluated. Models with resolution T42 performed more poorly than lower-resolution models. The higher resolution models were predominantly spectral. At low resolution, spectral versus gridpoint numerics performed with nearly equal verisimilitude. At low resolution, moisture convergence closure was slightly more preferable than other convective closure techniques. At high resolution, the models that used moisture convergence closure performed very poorly, suggesting that moisture convergence may be problematic for models with horizontal resolution T42.

Vegetation-rainfall feedbacks across the Sahel: a combined observational and modeling study

NASA Astrophysics Data System (ADS)

Yu, Y.; Notaro, M.; Wang, F.; Mao, J.; Shi, X.; Wei, Y.

2016-12-01

The Sahel rainfall is characterized by large interannual variability. Past modeling studies have concluded that the Sahel rainfall variability is primarily driven by oceanic forcings and amplified by land-atmosphere interactions. However, the relative importance of oceanic versus terrestrial drivers has never been assessed from observations. The current understanding of vegetation's impacts on climate, i.e. positive vegetation-rainfall feedback through the albedo, moisture, and momentum mechanisms, comes from untested models. Neither the positive vegetation-rainfall feedback, nor the underlying mechanisms, has been fully resolved in observations. The current study fills the knowledge gap about the observed vegetation-rainfall feedbacks, through the application of the multivariate statistical method Generalized Equilibrium Feedback Assessment (GEFA) to observational data. According to GEFA, the observed oceanic impacts dominate over terrestrial impacts on Sahel rainfall, except in the post-monsoon period. Positive leaf area index (LAI) anomalies favor an extended, wetter monsoon across the Sahel, largely due to moisture recycling. The albedo mechanism is not responsible for this positive vegetation feedback on the seasonal-interannual time scale, which is too short for a grass-desert transition. A low-level stabilization and subsidence is observed in response to increased LAI - potentially responsible for a negative vegetation-rainfall feedback. However, the positive moisture feedback overwhelms the negative momentum feedback, resulting in an observed positive vegetation-rainfall feedback. We further applied GEFA to a fully-coupled Community Earth System Model (CESM) control run, as an example of evaluating climate models against the GEFA-based observational benchmark. In contrast to the observed positive vegetation-rainfall feedbacks, CESM simulates a negative vegetation-rainfall feedback across Sahel, peaking in the pre-monsoon season. The simulated negative feedback is largely due to the low-level stabilization caused by increased LAI. Positive moisture feedback is present in the CESM simulation, but an order weaker than the observed and weaker than the negative momentum feedback, thereby leading to the simulated negative vegetation-rainfall feedbacks.

High resolution land surface response of inland moving Indian monsoon depressions over Bay of Bengal

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.

2016-05-01

During Indian summer monsoon (ISM) season, nearly about half of the monsoonal rainfall is brought inland by the low pressure systems called as Monsoon Depressions (MDs). These systems bear large amount of rainfall and frequently give copious amount of rainfall over land regions, therefore accurate forecast of these synoptic scale systems at short time scale can help in disaster management, flood relief, food safety. The goal of this study is to investigate, whether an accurate moisture-rainfall feedback from land surface can improve the prediction of inland moving MDs. High Resolution Land Data Assimilation System (HRLDAS) is used to generate improved land state .i.e. soil moisture and soil temperature profiles by means of NOAH-MP land-surface model. Validation of the model simulated basic atmospheric parameters at surface layer and troposphere reveals that the incursion of high resolution land state yields least Root Mean Squared Error (RMSE) with a higher correlation coefficient and facilitates accurate depiction of MDs. Rainfall verification shows that HRLDAS simulations are spatially and quantitatively in more agreement with the observations and the improved surface characteristics could result in the realistic reproduction of the storm spatial structure, movement as well as intensity. These results signify the necessity of investigating more into the land surface-rainfall feedbacks through modifications in moisture flux convergence within the storm.

Rainfall Downscaling Conditional on Upper-air Atmospheric Predictors: Improved Assessment of Rainfall Statistics in a Changing Climate

NASA Astrophysics Data System (ADS)

Langousis, Andreas; Mamalakis, Antonis; Deidda, Roberto; Marrocu, Marino

2015-04-01

To improve the level skill of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in reproducing the statistics of rainfall at a basin level and at hydrologically relevant temporal scales (e.g. daily), two types of statistical approaches have been suggested. One is the statistical correction of climate model rainfall outputs using historical series of precipitation. The other is the use of stochastic models of rainfall to conditionally simulate precipitation series, based on large-scale atmospheric predictors produced by climate models (e.g. geopotential height, relative vorticity, divergence, mean sea level pressure). The latter approach, usually referred to as statistical rainfall downscaling, aims at reproducing the statistical character of rainfall, while accounting for the effects of large-scale atmospheric circulation (and, therefore, climate forcing) on rainfall statistics. While promising, statistical rainfall downscaling has not attracted much attention in recent years, since the suggested approaches involved complex (i.e. subjective or computationally intense) identification procedures of the local weather, in addition to demonstrating limited success in reproducing several statistical features of rainfall, such as seasonal variations, the distributions of dry and wet spell lengths, the distribution of the mean rainfall intensity inside wet periods, and the distribution of rainfall extremes. In an effort to remedy those shortcomings, Langousis and Kaleris (2014) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables, which accurately reproduces the statistical character of rainfall at multiple time-scales. Here, we study the relative performance of: a) quantile-quantile (Q-Q) correction of climate model rainfall products, and b) the statistical downscaling scheme of Langousis and Kaleris (2014), in reproducing the statistical structure of rainfall, as well as rainfall extremes, at a regional level. This is done for an intermediate-sized catchment in Italy, i.e. the Flumendosa catchment, using climate model rainfall and atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com). In doing so, we split the historical rainfall record of mean areal precipitation (MAP) in 15-year calibration and 45-year validation periods, and compare the historical rainfall statistics to those obtained from: a) Q-Q corrected climate model rainfall products, and b) synthetic rainfall series generated by the suggested downscaling scheme. To our knowledge, this is the first time that climate model rainfall and statistically downscaled precipitation are compared to catchment-averaged MAP at a daily resolution. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the climate model used and the length of the calibration period. This is particularly the case for the yearly rainfall maxima, where direct statistical correction of climate model rainfall outputs shows increased sensitivity to the length of the calibration period and the climate model used. The robustness of the suggested downscaling scheme in modeling rainfall extremes at a daily resolution, is a notable feature that can effectively be used to assess hydrologic risk at a regional level under changing climatic conditions. Acknowledgments The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State. CRS4 highly acknowledges the contribution of the Sardinian regional authorities.

Proxy system modeling of tree-ring isotope chronologies over the Common Era

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; LeGrande, A. N.

2017-12-01

The Asian monsoon can be characterized in terms of both precipitation variability and atmospheric circulation across a range of spatial and temporal scales. While multicentury time series of tree-ring widths at hundreds of sites across Asia provide estimates of past rainfall, the oxygen isotope ratios of annual rings may reveal broader regional hydroclimate and atmosphere-ocean dynamics. Tree-ring oxygen isotope chronologies from Monsoon Asia have been interpreted to reflect a local 'amount effect', relative humidity, source water and seasonality, and winter snowfall. Here, we use an isotope-enabled general circulation model simulation from the NASA Goddard Institute for Space Science (GISS) Model E and a proxy system model of the oxygen isotope composition of tree-ring cellulose to interpret the large-scale and local climate controls on δ 18O chronologies. Broad-scale dominant signals are associated with a suite of covarying hydroclimate variables including growing season rainfall amounts, relative humidity, and vapor pressure deficit. Temperature and source water influences are region-dependent, as are the simulated tree-ring isotope signals associated with the El Nino Southern Oscillation (ENSO) and large-scale indices of the Asian monsoon circulation. At some locations, including southern coastal Viet Nam, local precipitation isotope ratios and the resulting simulated δ 18O tree-ring chronologies reflect upstream rainfall amounts and atmospheric circulation associated with monsoon strength and wind anomalies.

Internally Generated and Externally Forced Multidecadal Oceanic Modes and their Influence on the Summer Rainfall over East Asia

NASA Astrophysics Data System (ADS)

Si, D.; Hu, A.

2017-12-01

The interdecadal oceanic variabilities can be generated from both internal and external processes, and these variabilities can significantly modulate our climate on global and regional scale, such as the warming slowdown in the early 21st century, and the rainfall in East Asia. By analyzing simulations from a unique Community Earth System Model (CESM) Large Ensemble (CESM_LE) project, we show that the Interdecadal Pacific Oscillation (IPO) is primarily an internally generated oceanic variability, while the Atlantic Multidecadal Oscillation (AMO) may be an oceanic variability generated by internal oceanic processes and modulated by external forcings in the 20th century. Although the observed relationship between IPO and the Yangtze-Huaihe River valley (YHRV) summer rainfall in China is well simulated in both the preindustrial control and 20th century ensemble, none of the 20th century ensemble members can reproduce the observed time evolution of both IPO and YHRV due to the unpredictable nature of IPO on multidecade timescale. On the other hand, although CESM_LE cannot reproduce the observed relationship between AMO and Huanghe River valley (HRV) summer rainfall of China in the preindustrial control simulation, this relationship in the 20th century simulations is well reproduced, and the chance to reproduce the observed time evolution of both AMO and HRV rainfall is about 30%, indicating the important role of the interaction between the internal processes and the external forcing to realistically simulate the AMO and HRV rainfall.

Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

NASA Astrophysics Data System (ADS)

Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

2018-06-01

Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute to the understanding of the added value in seasonal simulations by RCMs.

Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

NASA Astrophysics Data System (ADS)

Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

2017-08-01

Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute to the understanding of the added value in seasonal simulations by RCMs.

Evaluation of different rainfall products over India for the summer monsoon

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis; Turner, Andrew; Collins, Mathew; AchutoRao, Krishna

2015-04-01

Summer rainfall over India forms an integral part of the Asian monsoon, which plays a key role in the global water cycle and climate system through coupled atmospheric and oceanic processes. Accurate prediction of Indian summer monsoon rainfall and its variability at various spatiotemporal scales are crucial for agriculture, water resources and hydroelectric-power sectors. Reliable rainfall observations are very important for verification of numerical model outputs and model development. However, high spatiotemporal variability of rainfall makes it difficult to measure adequately with ground-based instruments over a large region of various surface types from deserts to oceans. A number of multi-satellite rainfall products are available to users at different spatial and temporal scales. Each rainfall product has some advantages as well as limitations, hence it is essential to find a suitable region-specific data set among these rainfall products for a particular user application, such as water resources, agricultural modelling etc. In this study, we examine seasonal-mean and daily rainfall datasets for monsoon model validation. First, six multi-satellite and gauge-only rainfall products were evaluated over India at seasonal scale for 27 (JJAS 1979-2005) summer monsoon seasons against gridded 0.5-degree IMD gauge-based rainfall. Various skill metrics are computed to assess the potential of these data sets in representation of large-scale monsoon rainfall at all-India and sub-regional scales. Among the gauge-only data sets, APHRODITE and GPCC appear to outperform the others whereas GPCP is better than CMAP in the merged multi-satellite category. However, there are significant differences among these data sets indicating uncertainty in the observed rainfall over this region, with important implications for the evaluation of model simulations. At the daily scale, TRMM TMPA-3B42 is one of the best available products and is widely used for various hydro-meteorological applications. The existing version 6 (V6) products of TRMM underwent major changes and version 7 (V7) products were released in late 2012, and we compare these to the IMD daily gridded data over the 1998-2010 period. We show a clear improvement in V7 over V6 in the South Asian monsoon region using various skill metrics. Over typical monsoon rainfall zones, biases are improved by 5-10% in V7 over higher-rainfall regions. These results will help users to select appropriate rainfall product for their application. With the recent launch of the GPM Core Observatory, the release of a more advanced high-resolution multi-satellite rainfall product is expected soon.

Deciphering the expression of climate change within the Lower Colorado River basin by stochastic simulation of convective rainfall

NASA Astrophysics Data System (ADS)

Bliss Singer, Michael; Michaelides, Katerina

2017-10-01

In drylands, convective rainstorms typically control runoff, streamflow, water supply and flood risk to human populations, and ecological water availability at multiple spatial scales. Since drainage basin water balance is sensitive to climate, it is important to improve characterization of convective rainstorms in a manner that enables statistical assessment of rainfall at high spatial and temporal resolution, and the prediction of plausible manifestations of climate change. Here we present a simple rainstorm generator, STORM, for convective storm simulation. It was created using data from a rain gauge network in one dryland drainage basin, but is applicable anywhere. We employ STORM to assess watershed rainfall under climate change simulations that reflect differences in wetness/storminess, and thus provide insight into observed or projected regional hydrologic trends. Our analysis documents historical, regional climate change manifesting as a multidecadal decline in rainfall intensity, which we suggest has negatively impacted ephemeral runoff in the Lower Colorado River basin, but has not contributed substantially to regional negative streamflow trends.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

A comparison of methods to estimate future sub-daily design rainfall

NASA Astrophysics Data System (ADS)

Li, J.; Johnson, F.; Evans, J.; Sharma, A.

2017-12-01

Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.

Analysis of anthropogenic contributions to record high Australian summer rainfall (2010-2012) using CMIP5 simulations

NASA Astrophysics Data System (ADS)

Lewis, Sophie; Karoly, David

2013-04-01

Changes in extreme climate events pose significant challenges for both human and natural systems. Some climate extremes are likely to become "more frequent, more widespread and/or more intense during the 21st century" (Intergovernmental Panel on Climate Change, 2007) due to anthropogenic climate change. Particularly in Australia, El Niño-Southern Oscillation (ENSO) has a relationship to the relative frequency of temperature and precipitation extremes. In this study, we investigate the record high two-summer rainfall observed in Australia (2010-2011 and 2011-2012). This record rainfall occurred in association with a two year extended La Niña event and resulted in severe and extensive flooding. We examine simulated changes in seasonal-scale rainfall extremes in the Australian region in a suite of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). In particular, we utilise the novel CMIP5 detection and attribution historical experiments with various forcings (natural forcings only and greenhouse gas forcings only) to examine the impact of various anthropogenic forcings on seasonal-scale extreme rainfall across Australia. Using these standard detection and attribution experiments over the period of 1850 to 2005, we examine La Niña contributions to the 2-season record rainfall, as well as the longer-term climate change contribution to rainfall extremes. Was there an anthropogenic influence in the record high Australian summer rainfall over 2010 to 2012, and if so, how much influence? Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report on the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K.

Accounting for Rainfall Spatial Variability in Prediction of Flash Floods

NASA Astrophysics Data System (ADS)

Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.

2016-12-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Accounting for rainfall spatial variability in the prediction of flash floods

NASA Astrophysics Data System (ADS)

Saharia, Manabendra; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Vergara, Humberto; Flamig, Zachary L.

2017-04-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 15,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. The database has been subjected to rigorous quality control by accounting for radar beam height and percentage snow in basins. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Is there a stratospheric pacemaker controlling the daily cycle of tropical rainfall?

NASA Astrophysics Data System (ADS)

Sakazaki, T.; Hamilton, K.; Zhang, C.; Wang, Y.

2017-02-01

Rainfall in the tropics exhibits a large, 12 h Sun-synchronous variation with coherent phase around the globe. A long-standing, but unproved, hypothesis for this phenomenon is excitation by the prominent 12 h atmospheric tide, which itself is significantly forced remotely by solar heating of the stratospheric ozone layer. We investigated the relative roles of large-scale tidal forcing and more local effects in accounting for the 12 h variation of tropical rainfall. A model of the atmosphere run with the diurnal cycle of solar heating artificially suppressed below the stratosphere still simulated a strong coherent 12 h rainfall variation ( 50% of control run), demonstrating that stratospherically forced atmospheric tide propagates downward to the troposphere and contributes to the organization of large-scale convection. The results have implications for theories of excitation of tropical atmospheric waves by moist convection, for the evaluation of climate models, and for explaining the recently discovered lunar tidal rainfall cycle.

Future changes in Asian summer monsoon precipitation extremes as inferred from 20-km AGCM simulations

NASA Astrophysics Data System (ADS)

Lui, Yuk Sing; Tam, Chi-Yung; Lau, Ngar-Cheung

2018-04-01

This study examines the impacts of climate change on precipitation extremes in the Asian monsoon region during boreal summer, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model. The model can capture the summertime monsoon rainfall, with characteristics similar to those from Tropical Rainfall Measuring Mission and Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation. By comparing the 2075-2099 with the present-day climate simulations, there is a robust increase of the mean rainfall in many locations due to a warmer climate. Over southeastern China, the Baiu rainband, Bay of Bengal and central India, extreme precipitation rates are also enhanced in the future, which can be inferred from increases of the 95th percentile of daily precipitation, the maximum accumulated precipitation in 5 consecutive days, the simple daily precipitation intensity index, and the scale parameter of the fitted gamma distribution. In these regions, with the exception of the Baiu rainband, most of these metrics give a fractional change of extreme rainfall per degree increase of the lower-tropospheric temperature of 5 to 8.5% K-1, roughly consistent with the Clausius-Clapeyron relation. However, over the Baiu area extreme precipitation change scales as 3.5% K-1 only. We have also stratified the rainfall data into those associated with tropical cyclones (TC) and those with other weather systems. The AGCM gives an increase of the accumulated TC rainfall over southeastern China, and a decrease in southern Japan in the future climate. The latter can be attributed to suppressed TC occurrence in southern Japan, whereas increased accumulated rainfall over southeastern China is due to more intense TC rain rate under global warming. Overall, non-TC weather systems are the main contributor to enhanced precipitation extremes in various locations. In the future, TC activities over southeastern China tend to further exacerbate the precipitation extremes, whereas those in the Baiu region lead to weaker changes of these extremes.

Assessment of regional downscaling simulations for long term mean, excess and deficit Indian Summer Monsoons

NASA Astrophysics Data System (ADS)

Varikoden, Hamza; Mujumdar, M.; Revadekar, J. V.; Sooraj, K. P.; Ramarao, M. V. S.; Sanjay, J.; Krishnan, R.

2018-03-01

This study undertakes a comprehensive assessment of dynamical downscaling of summer monsoon (June-September; JJAS) rainfall over heterogeneous regions namely the Western Ghats (WG), Central India (CI) and North-Eastern Region (NER) for long term mean, excess and deficit episodes for the historical period from 1951 to 2005. This downscaling assessment is based on six Coordinated Regional Climate Downscaling Experiments (CORDEX) for South Asia (SAS) region, their five driving Global Climate Models (GCM) simulations along with observations from India Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Integrated Towards Evaluation for Water Resources (APHRODITE). The analysis reveals an overall reduction of dry bias in rainfall across the regions of Indian sub-continent in most of the downscaled CORDEX-SAS models and in their ensemble mean as compared to that of driving GCMs. The interannual variabilities during historical period are reasonably captured by the ensemble means of CORDEX-SAS simulations with an underestimation of 0.43%, 38% and 52% for the WG, CI and NER, respectively. Upon careful examination of the CORDEX-SAS models and their driving GCMs revealed considerable improvement in the regionally downscaled rainfall. The value addition of dynamical downscaling is apparent over the WG in Regional Climate Model (RCM) simulations with an improvement of more than 30% for the long term mean, excess and deficit episodes from their driving GCMs. In the case of NER, the improvement in the downscaled rainfall product is more than 10% for all the episodes. However, the value addition in the CORDEX-SAS simulations for CI region, dominantly influenced by synoptic scale processes, is not clear. Nevertheless, the reduction of dry bias in the complex topographical regions is remarkable. The relative performance of dynamical downscaling of rainfall over complex topography in response to local forcing and orographic lifting depict the value addition (30% over WG and 10% over NER, with a statistical significance of more than 5% level), when compared with the synoptic scale system induced rainfall over the plains of central-India.

Effects of Increased Horizontal Resolution on Simulation of the North American Monsoon in the NCAR CAM3: An Evaluation based on Surface, Satellite, and Reanalysis Data

NASA Astrophysics Data System (ADS)

Collier, J. C.; Zhang, G. J.

2006-05-01

Simulation of the North American monsoon system by the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM3) is evaluated in its sensitivity to increasing horizontal resolution. For two resolutions, T42 and T85, rainfall is compared to TRMM satellite-derived and surface gauge-based rainfall rates over the U.S. and northern Mexico as well as rainfall accumulations in gauges of the North American Monsoon Experiment (NAME) Enhanced Rain Gauge Network (NERN) in the Sierra Madre Occidental mountains. Simulated upper-tropospheric mass and wind fields are compared to those from NCEP-NCAR reanalyses. The comparison presented herein demonstrates that tropospheric motions associated with the North American monsoon system are sensitive to increasing the horizontal resolution of the model. An increase in resolution from T42 to T85 results in changes to a region of large-scale mid-tropospheric descent found north and east of the monsoon anticyclone. Relative to its simulation at T42, this region extends farther south and west at T85. Additionally, at T85, the subsidence is stronger. Consistent with the differences in large-scale descent, the T85 simulation of CAM3 is anomalously dry over Texas and northeastern Mexico during the peak monsoon months. Meanwhile, the geographic distribution of rainfall over the Sierra Madre Occidental region of Mexico is more satisfactorily simulated at T85 than at T42 for July and August. Moisture import into this region is greater at T85 than at T42 during these months. A focused study of the Sierra Madre Occidental region in particular shows that, in the regional average sense, the timing of the peak of the monsoon is relatively insensitive to the horizontal resolution of the model, while a phase bias in the diurnal cycle of monsoon-season precipitation is somewhat reduced in the higher-resolution run. At both resolutions, CAM3 poorly simulates the month-to-month evolution of monsoon rainfall over extreme northwestern Mexico and Arizona, though biases are considerably improved at T85.

Role of aerosols on the Indian Summer Monsoon variability, as simulated by state-of-the-art global climate models

NASA Astrophysics Data System (ADS)

Cagnazzo, Chiara; Biondi, Riccardo; D'Errico, Miriam; Cherchi, Annalisa; Fierli, Federico; Lau, William K. M.

2016-04-01

Recent observational and modeling analyses have explored the interaction between aerosols and the Indian summer monsoon precipitation on seasonal-to-interannual time scales. By using global scale climate model simulations, we show that when increased aerosol loading is found on the Himalayas slopes in the premonsoon period (April-May), intensification of early monsoon rainfall over India and increased low-level westerly flow follow, in agreement with the elevated-heat-pump (EHP) mechanism. The increase in rainfall during the early monsoon season has a cooling effect on the land surface that may also be amplified through solar dimming (SD) by more cloudiness and aerosol loading with subsequent reduction in monsoon rainfall over India. We extend this analyses to a subset of CMIP5 climate model simulations. Our results suggest that 1) absorbing aerosols, by influencing the seasonal variability of the Indian summer monsoon with the discussed time-lag, may act as a source of predictability for the Indian Summer Monsoon and 2) if the EHP and SD effects are operating also in a number of state-of-the-art climate models, their inclusion could potentially improve seasonal forecasts.

A Monte-Carlo Bayesian framework for urban rainfall error modelling

NASA Astrophysics Data System (ADS)

Ochoa Rodriguez, Susana; Wang, Li-Pen; Willems, Patrick; Onof, Christian

2016-04-01

Rainfall estimates of the highest possible accuracy and resolution are required for urban hydrological applications, given the small size and fast response which characterise urban catchments. While significant progress has been made in recent years towards meeting rainfall input requirements for urban hydrology -including increasing use of high spatial resolution radar rainfall estimates in combination with point rain gauge records- rainfall estimates will never be perfect and the true rainfall field is, by definition, unknown [1]. Quantifying the residual errors in rainfall estimates is crucial in order to understand their reliability, as well as the impact that their uncertainty may have in subsequent runoff estimates. The quantification of errors in rainfall estimates has been an active topic of research for decades. However, existing rainfall error models have several shortcomings, including the fact that they are limited to describing errors associated to a single data source (i.e. errors associated to rain gauge measurements or radar QPEs alone) and to a single representative error source (e.g. radar-rain gauge differences, spatial temporal resolution). Moreover, rainfall error models have been mostly developed for and tested at large scales. Studies at urban scales are mostly limited to analyses of propagation of errors in rain gauge records-only through urban drainage models and to tests of model sensitivity to uncertainty arising from unmeasured rainfall variability. Only few radar rainfall error models -originally developed for large scales- have been tested at urban scales [2] and have been shown to fail to well capture small-scale storm dynamics, including storm peaks, which are of utmost important for urban runoff simulations. In this work a Monte-Carlo Bayesian framework for rainfall error modelling at urban scales is introduced, which explicitly accounts for relevant errors (arising from insufficient accuracy and/or resolution) in multiple data sources (in this case radar and rain gauge estimates typically available at present), while at the same time enabling dynamic combination of these data sources (thus not only quantifying uncertainty, but also reducing it). This model generates an ensemble of merged rainfall estimates, which can then be used as input to urban drainage models in order to examine how uncertainties in rainfall estimates propagate to urban runoff estimates. The proposed model is tested using as case study a detailed rainfall and flow dataset, and a carefully verified urban drainage model of a small (~9 km2) pilot catchment in North-East London. The model has shown to well characterise residual errors in rainfall data at urban scales (which remain after the merging), leading to improved runoff estimates. In fact, the majority of measured flow peaks are bounded within the uncertainty area produced by the runoff ensembles generated with the ensemble rainfall inputs. REFERENCES: [1] Ciach, G. J. & Krajewski, W. F. (1999). On the estimation of radar rainfall error variance. Advances in Water Resources, 22 (6), 585-595. [2] Rico-Ramirez, M. A., Liguori, S. & Schellart, A. N. A. (2015). Quantifying radar-rainfall uncertainties in urban drainage flow modelling. Journal of Hydrology, 528, 17-28.

Simulating Daily and Sub-daily Water Flow in Large, Semi-arid Watershed Using SWAT: A Case Study of Nueces River Basin, Texas

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2015-12-01

Runoff generated during heavy rainfall imposes quick, but often intense, changes in the flow of streams, which increase the chance of flash floods in the vicinity of the streams. Understanding the temporal response of streams to heavy rainfall requires a hydrological model that considers meteorological, hydrological, and geological components of the streams and their watersheds. SWAT is a physically-based, semi-distributed model that is capable of simulating water flow within watersheds with both long-term, i.e. annually and monthly, and short-term (daily and sub-daily) time scales. However, the capability of SWAT in sub-daily water flow modeling within large watersheds has not been studied much, compare to long-term and daily time scales. In this study we are investigating the water flow in a large, semi-arid watershed, Nueces River Basin (NRB) with the drainage area of 16950 mi2 located in South Texas, with daily and sub-daily time scales. The objectives of this study are: (1) simulating the response of streams to heavy, and often quick, rainfall, (2) evaluating SWAT performance in sub-daily modeling of water flow within a large watershed, and (3) examining means for model performance improvement during model calibration and verification based on results of sensitivity and uncertainty analysis. The results of this study can provide important information for water resources planning during flood seasons.

A medium scale mobile rainfall simulator for experiments on soil erosion and soil hydrology

NASA Astrophysics Data System (ADS)

Kavka, Petr; Dostál, Tomáš; Iserloh, Thomas; Davidová, Tereza; Krása, Josef; David, Václav; Vopravil, Jan; Khel, Tomáš; Bauer, Miroslav

2015-04-01

Numerous types of rainfall simulators (RS) have been used to the study the behaviour of surface runoff and sediment transport caused by rainfall. It has been documented, that reproducibility and the knowledge of test conditions are essential for gathering necessary and comparable data. Therefore medium, to large scale field rainfall simulators are very desirable. Such devices are nevertheless very much time and laboratory consuming and their weakness is especially a high water consumption. A new, compact and mobile medium scale rainfall simulator has been developed under close cooperation of CTU Prague and Research Institute of Soil Conservation. The main idea was to develop a device, which is easily to handle by 4 persons, transportable with trailer behind an off-road car and independent of additional water sources and energy. Therefore, a special construction fixed on a standard trailer has been developed. It consists of an aggregate to produce power, an electric pump and a water tank with a capacity up to 1000 l. The pump can work in reverse mode, what allows filling the water tank from any source, including stream or pond. The capacity of the tank is normally sufficient for experiments with duration up to 30 minutes. The RS itself consist of a folding arm, which carries 4 nozzles (SS Full Jet 40WSQ), controlled by electromagnetic valves, which allow to set up desired rainfall intensity by opening intervals. A simple logical unit allows programming various schemes of operation of individual nozzles, to keep low pressure fluctuation in the system. The arm is first unfolded into total length of 9.6 m and then lifted up, using simple crab to its operation position which is 2.3 - 2.65 m above terrain surface. The distance between individual nozzles had been optimized based on number of calibrating experiments on 2.4 m. There is also special space at the trailer for transportation of metal sheets and collector (for experimental plot), additional equipment, tools and measurement devices. To prevent the wind effect, whole construction can be easily covered by tarpaulin. The experimental plot has a basic size of 9.5 x 2 m, however, we usually use only 8 x 2 m. The nozzles are fed with a water pressure of about 0.8 bars. Various schemes of opened nozzles allow varying rainfall intensities between 40 and 80 mm.h-1. Rainfall collectors were used to measure spatial rainfall distribution. The spatial rainfall distribution on the entire plot is higher than 80% (Christiansen-Uniformity Coefficient). Drop size distribution and drop fall velocities were analyzed by means of a Laser Precipitation Monitor (by Thies) with satisfactory results. The mean drop sizes ranging between 0.75 - 2.00 mm depending on applied intensity. Resulting kinetic energies ranging from 188 - 582 J m-2 mm-1. The measured rainfall variables show low fluctuations throughout the tests and are therefore reproducible in field investigations. The research has been supported by the research projects SGS14/180/OHK1/3T/11 and QJ330118.

Do Plot Studies Generate “Directionally” Correct Assessments of Field Level Phosphorus Losses?

USDA-ARS?s Scientific Manuscript database

The National P Research Project (NPRP) coordinated a tremendous amount of research at the plot scale to assess the influence of nutrient management on P transport at the fields scale. The objectives of this research were to determine of plot scale rainfall simulations could be used to assess P trans...

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

Required spatial resolution of hydrological models to evaluate urban flood resilience measures

NASA Astrophysics Data System (ADS)

Gires, A.; Giangola-Murzyn, A.; Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

2012-04-01

During a flood in urban area, several non-linear processes (rainfall, surface runoff, sewer flow, and sub-surface flow) interact. Fully distributed hydrological models are a useful tool to better understand these complex interactions between natural processes and man built environment. Developing an efficient model is a first step to improve the understanding of flood resilience in urban area. Given that the previously mentioned underlying physical phenomenon exhibit different relevant scales, determining the required spatial resolution of such model is tricky but necessary issue. For instance such model should be able to properly represent large scale effects of local scale flood resilience measures such as stop logs. The model should also be as simple as possible without being simplistic. In this paper we test two types of model. First we use an operational semi-distributed model over a 3400 ha peri-urban area located in Seine-Saint-Denis (North-East of Paris). In this model, the area is divided into sub-catchments of average size 17 ha that are considered as homogenous, and only the sewer discharge is modelled. The rainfall data, whose resolution is 1 km is space and 5 min in time, comes from the C-band radar of Trappes, located in the West of Paris, and operated by Météo-France. It was shown that the spatial resolution of both the model and the rainfall field did not enable to fully grasp the small scale rainfall variability. To achieve this, first an ensemble of realistic rainfall fields downscaled to a resolution of 100 m is generated with the help of multifractal space-time cascades whose characteristic exponents are estimated on the available radar data. Second the corresponding ensemble of sewer hydrographs is simulated by inputting each rainfall realization to the model. It appears that the probability distribution of the simulated peak flow exhibits a power-law behaviour. This indicates that there is a great uncertainty associated with small scale rainfall. Second we focus on a 50 ha catchment of this area and implement Multi-Hydro, a fully distributed urban hydrological model currently being developed at Ecole des Ponts ParisTech (El Tabach et al., 2009). The version used in this paper consists in an interactive coupling between a 2D model representing infiltration and surface runoff (TREX, Two dimensional Runoff, Erosion and eXport model, Velleux et al., 2011) and a 1D model of sewer networks (SWMM, Storm Water Management Model, Rossman, 2007). Spatial resolution ranging from 2 m to 50 m for land use, topography and rainfall are tested. A special highlight on the impact of small scales rainfall is done. To achieve this the previously mentioned methodology is implemented with rainfall fields downscaled to 10 m in space and 20 s in time. Finally, we will discuss the gains generated by the implementation of the fully distributed model.

Modelling soil erosion in rainfed vineyards of northeast of Spain under climate change: effects of increasing rainfall intensity

NASA Astrophysics Data System (ADS)

Concepción Ramos, Maria

2017-04-01

This aim of the research was to analyse the effect of rainfall distribution and intensity on soil erosion in vines cultivated in the Mediterranean under the projected climate change scenario. The simulations were done at plot scale using the WEPP model. Climatic data for the period 1996-2014 were obtained from a meteorological station located 6km far from the plot. Soil characteristics such as texture, organic matter content, water retention capacity and infiltration were analysed. Runoff and soil losses were measured at four locations within the plot during 4 years and used to calibrate and validate the model. According to evidences recorded in the area, changes of rainfall intensities of 10 and 20% were considered for different rainfall distributions. The simulations were extended to the predicted changes for 2030, 2050 and 2070 based on the HadGEM2-CC under the Representative Concentration Pathways (RCPs) 8.5 scenario. WEPP model provided a suitable prediction of the seasonal runoff and erosion as simulated relatively well the runoff and erosion of the most important events although some deficiencies were found for those events that produced low runoff. The simulation confirmed the contribution of the extreme events to annual erosion rates in 70%, on average. The model responded to changes in precipitation predicted under a climate change scenario with a decrease of runoff and erosion, and with higher erosion rates for an increase in rainfall intensity. A 10% increase may imply erosion rates up to 22% greater for the scenario 2030, and despite the predicted decrease in precipitation for the scenario 2050, soil losses may be up to 40% greater than at present for some rainfall distributions and intensity rainfall increases of 20%. These findings show the need of considering rainfall intensity as one of the main driven factors when soil erosion rates under climate change are predicted. Keywords: extreme events, rainfall distribution, runoff, soil losses, wines, WEPP.

Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; ...

2016-02-01

This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super-Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual-mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double-ITCZ bias. However, unfolding intensity distributions reveal several improvementsmore » in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden-Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM’s low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved-scale processes in CAM, few differences discriminate the rainfall properties of the two models. Lastly, these results are discussed in light of their implication for future rainfall changes in response to climate forcing.« less

Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

2017-04-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

Adjusting Satellite Rainfall Error in Mountainous Areas for Flood Modeling Applications

NASA Astrophysics Data System (ADS)

Zhang, X.; Anagnostou, E. N.; Astitha, M.; Vergara, H. J.; Gourley, J. J.; Hong, Y.

2014-12-01

This study aims to investigate the use of high-resolution Numerical Weather Prediction (NWP) for evaluating biases of satellite rainfall estimates of flood-inducing storms in mountainous areas and associated improvements in flood modeling. Satellite-retrieved precipitation has been considered as a feasible data source for global-scale flood modeling, given that satellite has the spatial coverage advantage over in situ (rain gauges and radar) observations particularly over mountainous areas. However, orographically induced heavy precipitation events tend to be underestimated and spatially smoothed by satellite products, which error propagates non-linearly in flood simulations.We apply a recently developed retrieval error and resolution effect correction method (Zhang et al. 2013*) on the NOAA Climate Prediction Center morphing technique (CMORPH) product based on NWP analysis (or forecasting in the case of real-time satellite products). The NWP rainfall is derived from the Weather Research and Forecasting Model (WRF) set up with high spatial resolution (1-2 km) and explicit treatment of precipitation microphysics.In this study we will show results on NWP-adjusted CMORPH rain rates based on tropical cyclones and a convective precipitation event measured during NASA's IPHEX experiment in the South Appalachian region. We will use hydrologic simulations over different basins in the region to evaluate propagation of bias correction in flood simulations. We show that the adjustment reduced the underestimation of high rain rates thus moderating the strong rainfall magnitude dependence of CMORPH rainfall bias, which results in significant improvement in flood peak simulations. Further study over Blue Nile Basin (western Ethiopia) will be investigated and included in the presentation. *Zhang, X. et al. 2013: Using NWP Simulations in Satellite Rainfall Estimation of Heavy Precipitation Events over Mountainous Areas. J. Hydrometeor, 14, 1844-1858.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, Pardeep; Patricola, Christina; Wehner, Michael; Stone, Dáithí; Paciorek, Christopher; Collins, William

2015-04-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods across the South Platte River basin impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling an 'event that was' for September 2013 and comparing it to a modelled 'event that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'event that was' simulations with the regional Weather Research and Forecasting (WRF) model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'event that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. Our model results suggests that, given an insignificant change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the probability of heavy rainfall occurring over the South Platte River basin in September 2013.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, P.; Patricola, C. M.; Wehner, M. F.; Stone, D. A.; Paciorek, C. J.; Collins, W.

2014-12-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling a 'world that was' for September 2013 and comparing it to a modelled 'world that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'world that was' simulations with the regional WRF model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'world that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. For example, preliminary analysis suggests that, given no change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the odds of heavy rainfall over the Front Range.

On the influence of simulated SST warming on rainfall projections in the Indo-Pacific domain: an AGCM study

NASA Astrophysics Data System (ADS)

Zhang, Huqiang; Zhao, Y.; Moise, A.; Ye, H.; Colman, R.; Roff, G.; Zhao, M.

2018-02-01

Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20-25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying SST forcing.

Comparison of TOPMODEL streamflow simulations using NEXRAD-based and measured rainfall data, McTier Creek watershed, South Carolina

USGS Publications Warehouse

Feaster, Toby D.; Westcott, Nancy E.; Hudson, Robert J.M.; Conrads, Paul; Bradley, Paul M.

2012-01-01

Rainfall is an important forcing function in most watershed models. As part of a previous investigation to assess interactions among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations in the Edisto River Basin, the topography-based hydrological model (TOPMODEL) was applied in the McTier Creek watershed in Aiken County, South Carolina. Measured rainfall data from six National Weather Service (NWS) Cooperative (COOP) stations surrounding the McTier Creek watershed were used to calibrate the McTier Creek TOPMODEL. Since the 1990s, the next generation weather radar (NEXRAD) has provided rainfall estimates at a finer spatial and temporal resolution than the NWS COOP network. For this investigation, NEXRAD-based rainfall data were generated at the NWS COOP stations and compared with measured rainfall data for the period June 13, 2007, to September 30, 2009. Likewise, these NEXRAD-based rainfall data were used with TOPMODEL to simulate streamflow in the McTier Creek watershed and then compared with the simulations made using measured rainfall data. NEXRAD-based rainfall data for non-zero rainfall days were lower than measured rainfall data at all six NWS COOP locations. The total number of concurrent days for which both measured and NEXRAD-based data were available at the COOP stations ranged from 501 to 833, the number of non-zero days ranged from 139 to 209, and the total difference in rainfall ranged from -1.3 to -21.6 inches. With the calibrated TOPMODEL, simulations using NEXRAD-based rainfall data and those using measured rainfall data produce similar results with respect to matching the timing and shape of the hydrographs. Comparison of the bias, which is the mean of the residuals between observed and simulated streamflow, however, reveals that simulations using NEXRAD-based rainfall tended to underpredict streamflow overall. Given that the total NEXRAD-based rainfall data for the simulation period is lower than the total measured rainfall at the NWS COOP locations, this bias would be expected. Therefore, to better assess the use of NEXRAD-based rainfall estimates as compared to NWS COOP rainfall data on the hydrologic simulations, TOPMODEL was recalibrated and updated simulations were made using the NEXRAD-based rainfall data. Comparisons of observed and simulated streamflow show that the TOPMODEL results using measured rainfall data and NEXRAD-based rainfall are comparable. Nonetheless, TOPMODEL simulations using NEXRAD-based rainfall still tended to underpredict total streamflow volume, although the magnitude of differences were similar to the simulations using measured rainfall. The McTier Creek watershed was subdivided into 12 subwatersheds and NEXRAD-based rainfall data were generated for each subwatershed. Simulations of streamflow were generated for each subwatershed using NEXRAD-based rainfall and compared with subwatershed simulations using measured rainfall data, which unlike the NEXRAD-based rainfall were the same data for all subwatersheds (derived from a weighted average of the six NWS COOP stations surrounding the basin). For the two simulations, subwatershed streamflow were summed and compared to streamflow simulations at two U.S. Geological Survey streamgages. The percentage differences at the gage near Monetta, South Carolina, were the same for simulations using measured rainfall data and NEXRAD-based rainfall. At the gage near New Holland, South Carolina, the percentage differences using the NEXRAD-based rainfall were twice as much as those using the measured rainfall. Single-mass curve comparisons showed an increase in the total volume of rainfall from north to south. Similar comparisons of the measured rainfall at the NWS COOP stations showed similar percentage differences, but the NEXRAD-based rainfall variations occurred over a much smaller distance than the measured rainfall. Nonetheless, it was concluded that in some cases, using NEXRAD-based rainfall data in TOPMODEL streamflow simulations may provide an effective alternative to using measured rainfall data. For this investigation, however, TOPMODEL streamflow simulations using NEXRAD-based rainfall data for both calibration and simulations did not show significant improvements with respect to matching observed streamflow over simulations generated using measured rainfall data.

Development and implementation of a laboratory spray device and rainfall simulator for retention research using small amounts of agroformulations.

PubMed

Zwertvaegher, Ingrid Ka; Van Daele, Inge; Verheesen, Peter; Peferoen, Marnix; Nuyttens, David

2017-01-01

Rainfall greatly affects the retention of foliar-applied agroformulations. Improving their resistance to wash-off is therefore of great importance in spray applications. When developing such formulations, small-scale laboratory assays are generally required. A set-up for retention studies using only small amounts of agroformulations (<0.5 L) was developed. The set-up consists of a spray device and a rainfall simulator. The effect of rain quantity (1, 3, 6 mm) on the spray retention of agroformulations was evaluated using this set-up. The data showed that uniform and repeatable spraying was achieved with the small-scale spray device (coefficient of variation 23.4%) on potato pot plants (Solanum tuberosum L.). Rain quantity significantly affected the spray retention. Approximately 40% of the initial deposition was lost after 1 mm of rain at an intensity of 25 mm h -1 . Additional losses decreased with increasing volumes of rain (65 and 80% loss after 3 and 6 mm of rain respectively). Future studies could implement the set-up to evaluate the effect of different rainfall characteristics and formulations on spray retention in order to improve the rainfastness of agroformulations. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Modelling landscape evolution at the flume scale

NASA Astrophysics Data System (ADS)

Cheraghi, Mohsen; Rinaldo, Andrea; Sander, Graham C.; Barry, D. Andrew

2017-04-01

The ability of a large-scale Landscape Evolution Model (LEM) to simulate the soil surface morphological evolution as observed in a laboratory flume (1-m × 2-m surface area) was investigated. The soil surface was initially smooth, and was subjected to heterogeneous rainfall in an experiment designed to avoid rill formation. Low-cohesive fine sand was placed in the flume while the slope and relief height were 5 % and 20 cm, respectively. Non-uniform rainfall with an average intensity of 85 mm h-1 and a standard deviation of 26 % was applied to the sediment surface for 16 h. We hypothesized that the complex overland water flow can be represented by a drainage discharge network, which was calculated via the micro-morphology and the rainfall distribution. Measurements included high resolution Digital Elevation Models that were captured at intervals during the experiment. The calibrated LEM captured the migration of the main flow path from the low precipitation area into the high precipitation area. Furthermore, both model and experiment showed a steep transition zone in soil elevation that moved upstream during the experiment. We conclude that the LEM is applicable under non-uniform rainfall and in the absence of surface incisions, thereby extending its applicability beyond that shown in previous applications. Keywords: Numerical simulation, Flume experiment, Particle Swarm Optimization, Sediment transport, River network evolution model.

Use of Fuzzy rainfall-runoff predictions for claypan watersheds with conservation buffers in Northeast Missouri

USDA-ARS?s Scientific Manuscript database

Despite increased interest in watershed scale model simulations, literature lacks application of long-term data in fuzzy logic simulations and comparing outputs with physically based models such as APEX (Agricultural Policy Environmental eXtender). The objective of this study was to develop a fuzzy...

The wildgeographer avatar shows how to measure soil erosion rates by means of a rainfall simulator

NASA Astrophysics Data System (ADS)

Cerdà, Artemi; González Pelayo, Óscar; Pereira, Paulo; Novara, Agata; Iserloh, Thomas; Prosdocimi, Massimo

2015-04-01

This contribution to the immersed worlds wish to develop the avatar that will teach the students and other scientists how to develop measurements of soil erosion, surface runoff and wetting fronts by means of simulated rainfall experiments. Rainfall simulation is a well established and knows methodology to measure the soil erosion rates and soil hydrology under controlled conditions (Cerdà 1998a; Cerdà, 1998b; Cerdà and Jurgensen, 2011; Dunkerley, 2012; Iserloh et al., 2012; Iserloh et al., 2013; Ziadat and Taimeh, 2013; Butzen et al., 2014). However, is a method that requires a long training and expertise to avoid mismanagement and mistaken. To use and avatar can help in the teaching of the technique and the dissemination of the findings. This contribution will show to other avatars how to develop an experiment with simulated rainfall and will help to take the right decision in the design of the experiments. Following the main parts of the experiments and measurements the Wildgeographer avatar must develop: 1. Determine the objectives and decide which rainfall intensity and distribution, and which plot size to be used. Choose between a laboratory or a field rainfall simulation. 2. Design of the rainfall simulator to achieve the objectives: type of rainfall simulator (sprayer or drop former) and calibrate. 3. The experiments are carried out. 4. The results are show. Acknowledgements To the "Ministerio de Economía and Competitividad" of Spanish Government for finance the POSTFIRE project (CGL2013- 47862-C2-1-R). The research projects GL2008-02879/BTE, LEDDRA 243857 and PREVENTING AND REMEDIATING DEGRADATION OF SOILS IN EUROPE THROUGH LAND CARE (RECARE)FP7-ENV-2013- supported this research. References Butzen, V., Seeger, M., Wirtz, S., Huemann, M., Mueller, C., Casper, M., Ries, J. B. 2014. Quantification of Hortonian overland flow generation and soil erosion in a Central European low mountain range using rainfall experiments. Catena, 113, 202-212. Cerdà, A. 1998a. Effect of climate on surface flow along a climatological gradient in Israel. A field rainfall simulation approach. Journal of Arid Environments, 38, 145-159. Cerdà, A. 1998b. The influence of aspect and vegetation on seasonal changes in erosion under rainfall simulation on a clay soil in Spain. Canadian Journal of Soil Science, 78, 321-330. Cerdà, A., Jurgensen, M. F. 2011. Ant mounds as a source of sediment on citrus orchard plantations in eastern Spain. A three-scale rainfall simulation approach. Catena, 85(3), 231-236. Dunkerley, D. 2012. Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils, Fowlers Gap, Australia. Hydrological Processes, 26(15), 2211-2224. Iserloh, T., Ries, J.B., Arnaez, J., Boix Fayos, C., Butzen, V., Cerdà, A., Echeverría, M.T., Fernández-Gálvez, J., Fister, W., Geißler, C., Gómez, J.A., Gómez-Macpherson, H., Kuhn, N.J., Lázaro, R., León, F.J., Martínez-Mena, M., Martínez-Murillo, J.F., Marzen, M., Mingorance, M.D., Ortigosa, L., Peters, P., Regüés, D., Ruiz-Sinoga, J.D., Scholten, T., Seeger, M., Solé-Benet, A., Wengel, R., Wirtz, S. 2013. European small portable rainfall simulators: a comparison of rainfall characteristics. Catena, 110, 100-112. Doi: 10.1016/j.catena.2013.05.013 Iserloh, T., Ries, J.B., Cerdà, A., Echeverría, M.T., Fister, W., Geißler, C., Kuhn, N.J., León, F.J., Peters, P., Schindewolf, M., Schmidt, J., Scholten, T., Seeger, M. (2012): Comparative measurements with seven rainfall simulators on uniform bare fallow land. Zeitschrift für Geomorphologie, 57, 193-201. DOI: 10.1127/0372- 8854/2012/S-00118. Ziadat, F. M., Taimeh, A. Y. 2013. Effect of rainfall intensity, slope and land use and antecedent soil moisture on soil erosion in an arid environment. Land Degradation & Development, 24: 582- 590. DOI 10.1002/ldr.2239

Impacts of drought on grape yields in Western Cape, South Africa

NASA Astrophysics Data System (ADS)

Araujo, Julio A.; Abiodun, Babatunde J.; Crespo, Olivier

2016-01-01

Droughts remain a threat to grape yields in South Africa. Previous studies on the impacts of climate on grape yield in the country have focussed on the impact of rainfall and temperature separately; meanwhile, grape yields are affected by drought, which is a combination of rainfall and temperature influences. The present study investigates the impacts of drought on grape yields in the Western Cape (South Africa) at district and farm scales. The study used a new drought index that is based on simple water balance (Standardized Precipitation Evapotranspiration Index; hereafter, SPEI) to identify drought events and used a correlation analysis to identify the relationship between drought and grape yields. A crop simulation model (Agricultural Production Systems sIMulator, APSIM) was applied at the farm scale to investigate the role of irrigation in mitigating the impacts of drought on grape yield. The model gives a realistic simulation of grape yields. The Western Cape has experienced a series of severe droughts in the past few decades. The severe droughts occurred when a decrease in rainfall occurred simultaneously with an increase in temperature. El Niño Southern Oscillation (ENSO) appears to be an important driver of drought severity in the Western Cape, because most of the severe droughts occurred in El Niño years. At the district scale, the correlation between drought index and grape yield is weak ( r≈-0.5), but at the farm scale, it is strong ( r≈-0.9). This suggests that many farmers are able to mitigate the impacts of drought on grape yields through irrigation management. At the farm scale, where the impact of drought on grape yields is high, poor yield years coincide with moderate or severe drought periods. The APSIM simulation, which gives a realistic simulation of grape yields at the farm scale, suggests that grape yields become more sensitive to spring and summer droughts in the absence of irrigation. Results of this study may guide decision-making on how to reduce the impacts of drought on food security in South Africa.

Pluviometric characterization of the Coca river basin by using a stochastic rainfall model

NASA Astrophysics Data System (ADS)

González-Zeas, Dunia; Chávez-Jiménez, Adriadna; Coello-Rubio, Xavier; Correa, Ángel; Martínez-Codina, Ángela

2014-05-01

An adequate design of the hydraulic infrastructures, as well as, the prediction and simulation of a river basin require historical records with a greater temporal and spatial resolution. However, the lack of an extensive network of precipitation data, the short time scale data and the incomplete information provided by the available rainfall stations limit the analysis and design of complex hydraulic engineering systems. As a consequence, it is necessary to develop new quantitative tools in order to face this obstacle imposed by ungauged or poorly gauged basins. In this context, the use of a spatial-temporal rainfall model allows to simulate the historical behavior of the precipitation and at the same time, to obtain long-term synthetic series that preserve the extremal behavior. This paper provides a characterization of the precipitation in the Coca river basin located in Ecuador by using RainSim V3, a robust and well tested stochastic rainfall model based on a spatial-temporal Neyman-Scott rectangular pulses process. A preliminary consistency analysis of the historical rainfall data available has been done in order to identify climatic regions with similar precipitation behavior patterns. Mean and maximum yearly and monthly fields of precipitation of high resolution spaced grids have been obtained through the use of interpolation techniques. According to the climatological similarity, long time series of daily temporal resolution of precipitation have been generated in order to evaluate the model skill in capturing the structure of daily observed precipitation. The results show a good performance of the model in reproducing very well the gross statistics, including the extreme values of rainfall at daily scale. The spatial pattern represented by the observed and simulated precipitation fields highlights the existence of two important regions characterized by different pluviometric comportment, with lower precipitation in the upper part of the basin and higher precipitation in the lower part of the basin.

Runoff simulation sensitivity to remotely sensed initial soil water content

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Schmugge, T. J.; Jackson, T. J.; Unkrich, C. L.; Keefer, T. O.; Parry, R.; Bach, L. B.; Amer, S. A.

1994-05-01

A variety of aircraft remotely sensed and conventional ground-based measurements of volumetric soil water content (SW) were made over two subwatersheds (4.4 and 631 ha) of the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed during the 1990 monsoon season. Spatially distributed soil water contents estimated remotely from the NASA push broom microwave radiometer (PBMR), an Institute of Radioengineering and Electronics (IRE) multifrequency radiometer, and three ground-based point methods were used to define prestorm initial SW for a distributed rainfall-runoff model (KINEROS; Woolhiser et al., 1990) at a small catchment scale (4.4 ha). At a medium catchment scale (631 ha or 6.31 km2) spatially distributed PBMR SW data were aggregated via stream order reduction. The impacts of the various spatial averages of SW on runoff simulations are discussed and are compared to runoff simulations using SW estimates derived from a simple daily water balance model. It was found that at the small catchment scale the SW data obtained from any of the measurement methods could be used to obtain reasonable runoff predictions. At the medium catchment scale, a basin-wide remotely sensed average of initial water content was sufficient for runoff simulations. This has important implications for the possible use of satellite-based microwave soil moisture data to define prestorm SW because the low spatial resolutions of such sensors may not seriously impact runoff simulations under the conditions examined. However, at both the small and medium basin scale, adequate resources must be devoted to proper definition of the input rainfall to achieve reasonable runoff simulations.

Modeling Rainfall-Runoff Dynamics in Tropical, Urban Socio-Hydrological Systems: Green Infrastructure and Variable Precipitation Interception

NASA Astrophysics Data System (ADS)

Nytch, C. J.; Meléndez-Ackerman, E. J.

2014-12-01

There is a pressing need to generate spatially-explicit models of rainfall-runoff dynamics in the urban humid tropics that can characterize flow pathways and flood magnitudes in response to erratic precipitation events. To effectively simulate stormwater runoff processes at multiple scales, complex spatio-temporal parameters such as rainfall, evapotranspiration, and antecedent soil moisture conditions must be accurately represented, in addition to uniquely urban factors including stormwater conveyance structures and connectivity between green and gray infrastructure elements. In heavily urbanized San Juan, Puerto Rico, stream flashiness and frequent flooding are major issues, yet still lacking is a hydrological analysis that models the generation and movement of fluvial and pluvial stormwater through the watershed. Our research employs a novel and multifaceted approach to dealing with this problem that integrates 1) field-based rainfall interception and infiltration methodologies to quantify the hydrologic functions of natural and built infrastructure in San Juan; 2) remote sensing analysis to produce a fine-scale typology of green and gray cover types in the city and determine patterns of spatial distribution and connectivity; 3) assessment of precipitation and streamflow variability at local and basin-wide scales using satellite and radar precipitation estimates in concert with rainfall and stream gauge point data and participatory flood mapping; 4) simulation of historical, present-day, and future stormwater runoff scenarios with a fully distributed hydrologic model that couples diverse components of urban socio-hydrological systems from formal and informal knowledge sources; and 5) bias and uncertainty analysis of parameters and model structure within a Bayesian hierarchical framework. Preliminary results from the rainfall interception study suggest that canopy structure and leaf area index of different tree species contribute to variable throughfall and stemflow responses. Additional investigations are pending. The findings from this work will help inform urban planning and design, and build adaptive capacity to reduce flood vulnerability in the context of a changing climate.

Thermodynamic sensitivities in observed and simulated extreme-rain-producing mesoscale convective systems

NASA Astrophysics Data System (ADS)

Schumacher, R. S.; Peters, J. M.

2015-12-01

Mesoscale convective systems (MCSs) are responsible for a large fraction of warm-season extreme rainfall events over the continental United States, as well as other midlatitude regions globally. The rainfall production in these MCSs is determined by numerous factors, including the large-scale forcing for ascent, the organization of the convection, cloud microphysical processes, and the surrounding thermodynamic and kinematic environment. Furthermore, heavy-rain-producing MCSs are most common at night, which means that well-studied mechanisms for MCS maintenance and organization such as cold pools (gravity currents) are not always at work. In this study, we use numerical model simulations and recent field observations to investigate the sensitivity of low-level MCS structures, and their influences on rainfall, to the details of the thermodynamic environment. In particular, small alterations to the initial conditions in idealized and semi-idealized simulations result in comparatively large precipitation changes, both in terms of the intensity and the spatial distribution. The uncertainties in the thermodynamic enviroments in the model simulations will be compared with high-resolution observations from the Plains Elevated Convection At Night (PECAN) field experiment in 2015. The results have implications for the paradigms of "surface-based" versus "elevated" convection, as well as for the predictability of warm-season convective rainfall.

South American climate during the Last Glacial Maximum: Delayed onset of the South American monsoon

NASA Astrophysics Data System (ADS)

Cook, K. H.; Vizy, E. K.

2006-01-01

The climate of the Last Glacial Maximum (LGM) over South America is simulated using a regional climate model with 60-km resolution, providing a simulation that is superior to those available from global models that do not resolve the topography and regional-scale features of the South American climate realistically. LGM conditions on SST, insolation, vegetation, and reduced atmospheric CO2 on the South American climate are imposed together and individually. Remote influences are not included. Annual rainfall is 25-35% lower in the LGM than in the present day simulation throughout the Amazon basin. A primary cause is a 2-3 month delay in the onset of the rainy season, so that the dry season is about twice as long as in the present day. The delayed onset occurs because the low-level inflow from the tropical Atlantic onto the South American continent is drier than in the present day simulation due to reduced evaporation from cooler surface waters, and this slows the springtime buildup of moist static energy that is needed to initiate convection. Once the monsoon begins in the Southern Hemisphere, LGM rainfall rates are similar to those in the present day. In the Northern Hemisphere, however, rainfall is lower throughout the (shortened) rainy season. Regional-scale structure includes slight precipitation increases in the Nordeste region of Brazil and along the eastern foothills of the Andes, and a region in the center of the Amazon basin that does not experience annual drying. In the Andes Mountains, the signal is complicated, with regions of significant rainfall increases adjacent to regions with reduced precipitation.

Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall-runoff model

NASA Astrophysics Data System (ADS)

Aronica, G. T.; Candela, A.

2007-12-01

SummaryIn this paper a Monte Carlo procedure for deriving frequency distributions of peak flows using a semi-distributed stochastic rainfall-runoff model is presented. The rainfall-runoff model here used is very simple one, with a limited number of parameters and practically does not require any calibration, resulting in a robust tool for those catchments which are partially or poorly gauged. The procedure is based on three modules: a stochastic rainfall generator module, a hydrologic loss module and a flood routing module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for a fixed duration, is assumed to follow the two components extreme value (TCEV) distribution whose parameters have been estimated at regional scale for Sicily. The catchment response has been modelled by using the Soil Conservation Service-Curve Number (SCS-CN) method, in a semi-distributed form, for the transformation of total rainfall to effective rainfall and simple form of IUH for the flood routing. Here, SCS-CN method is implemented in probabilistic form with respect to prior-to-storm conditions, allowing to relax the classical iso-frequency assumption between rainfall and peak flow. The procedure is tested on six practical case studies where synthetic FFC (flood frequency curve) were obtained starting from model variables distributions by simulating 5000 flood events combining 5000 values of total rainfall depth for the storm duration and AMC (antecedent moisture conditions) conditions. The application of this procedure showed how Monte Carlo simulation technique can reproduce the observed flood frequency curves with reasonable accuracy over a wide range of return periods using a simple and parsimonious approach, limited data input and without any calibration of the rainfall-runoff model.

Studies of regional-scale climate variability and change. Hidden Markov models and coupled ocean-atmosphere modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghil, M.; Kravtsov, S.; Robertson, A. W.

2008-10-14

This project was a continuation of previous work under DOE CCPP funding, in which we had developed a twin approach of probabilistic network (PN) models (sometimes called dynamic Bayesian networks) and intermediate-complexity coupled ocean-atmosphere models (ICMs) to identify the predictable modes of climate variability and to investigate their impacts on the regional scale. We had developed a family of PNs (similar to Hidden Markov Models) to simulate historical records of daily rainfall, and used them to downscale GCM seasonal predictions. Using an idealized atmospheric model, we had established a novel mechanism through which ocean-induced sea-surface temperature (SST) anomalies might influencemore » large-scale atmospheric circulation patterns on interannual and longer time scales; we had found similar patterns in a hybrid coupled ocean-atmosphere-sea-ice model. The goal of the this continuation project was to build on these ICM results and PN model development to address prediction of rainfall and temperature statistics at the local scale, associated with global climate variability and change, and to investigate the impact of the latter on coupled ocean-atmosphere modes. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling together with the development of associated software; new intermediate coupled models; a new methodology of inverse modeling for linking ICMs with observations and GCM results; and, observational studies of decadal and multi-decadal natural climate results, informed by ICM results.« less

Regional climate modeling over the Maritime Continent: Assessment of RegCM3-BATS1e and RegCM3-IBIS

NASA Astrophysics Data System (ADS)

Gianotti, R. L.; Zhang, D.; Eltahir, E. A.

2010-12-01

Despite its importance to global rainfall and circulation processes, the Maritime Continent remains a region that is poorly simulated by climate models. Relatively few studies have been undertaken using a model with fine enough resolution to capture the small-scale spatial heterogeneity of this region and associated land-atmosphere interactions. These studies have shown that even regional climate models (RCMs) struggle to reproduce the climate of this region, particularly the diurnal cycle of rainfall. This study builds on previous work by undertaking a more thorough evaluation of RCM performance in simulating the timing and intensity of rainfall over the Maritime Continent, with identification of major sources of error. An assessment was conducted of the Regional Climate Model Version 3 (RegCM3) used in a coupled system with two land surface schemes: Biosphere Atmosphere Transfer System Version 1e (BATS1e) and Integrated Biosphere Simulator (IBIS). The model’s performance in simulating precipitation was evaluated against the 3-hourly TRMM 3B42 product, with some validation provided of this TRMM product against ground station meteorological data. It is found that the model suffers from three major errors in the rainfall histogram: underestimation of the frequency of dry periods, overestimation of the frequency of low intensity rainfall, and underestimation of the frequency of high intensity rainfall. Additionally, the model shows error in the timing of the diurnal rainfall peak, particularly over land surfaces. These four errors were largely insensitive to the choice of boundary conditions, convective parameterization scheme or land surface scheme. The presence of a wet or dry bias in the simulated volumes of rainfall was, however, dependent on the choice of convection scheme and boundary conditions. This study also showed that the coupled model system has significant error in overestimation of latent heat flux and evapotranspiration from the land surface, and specifically overestimation of interception loss with concurrent underestimation of transpiration, irrespective of the land surface scheme used. Discussion of the origin of these errors is provided, with some suggestions for improvement.

Effect of monthly areal rainfall uncertainty on streamflow simulation

NASA Astrophysics Data System (ADS)

Ndiritu, J. G.; Mkhize, N.

2017-08-01

Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic monthly rainfalls were 86 and 90% of the mean naturalised streamflow. In calibration, 33% of the naturalised flow located within the streamflow ranges with historic rainfall simulations and using stochastic rainfalls increased this to 66%. In validation the respective percentages of naturalised flows located within the simulated streamflow ranges were 32 and 72% respectively. The analysis reveals that monthly areal rainfall uncertainty is significant and incorporating it into streamflow simulation would add validity to the results.

Centrifuge Modeling of Rainfall Induced Slope Failure

NASA Astrophysics Data System (ADS)

Ling, H.; Wu, M.

2006-12-01

Rainfall induces slope failure and debris flow which are considered as one of the major natural disasters. The scope of such failure is very large and it cannot be studied easily in the laboratory. Traditionally, small scale model tests are used to study such problem. Knowing that the behavior of soil is affected by the stress level, centrifuge modeling technique has been used to simulate more realistically full scale earth structures. In this study, two series of tests were conducted on slopes under the centrifugal field with and without the presence of rainfall. The soil used was a mixture of sand and 15 percent fines. The slopes of angle 60 degrees were prepared at optimum water content in order to achieve the maximum density. In the first series of tests, three different slope heights of 10 cm, 15 cm and 20 cm were used. The gravity was increased gradually until slope failure in order to obtain the prototype failure height. The slope model was cut after the test in order to obtain the configuration of failure surface. It was found that the slope geometry normalized by the height at failure provided unique results. Knowing the slope height or gravity at failure, the second series of tests with rainfall were conducted slightly below the critical height. That is, after attaining the desired gravity, the rainfall was induced in the centrifuge. Special nozzles were used and calibrated against different levels of gravity in order to obtain desired rainfall intensity. Five different rainfall intensities were used on the 15-cm slopes at 80g and 60g, which corresponded to 12 m and 9 m slope height, respectively. The duration until failure for different rainfall intensities was obtained. Similar to the first series of tests, the slope model was cut and investigated after the test. The results showed that the failure surface was not significantly affected by the rainfall. That is, the excess pore pressure induced by rainfall generated slope failure. The prediction curves of rainfall intensity versus duration were obtained from the test results. Such curves are extremely useful for disaster management. This study indicated feasibilities of using centrifuge modeling technique in simulating rainfall induced slope failure. The results obtained may also be used for validating numerical tools.

CMIP5 ensemble-based spatial rainfall projection over homogeneous zones of India

NASA Astrophysics Data System (ADS)

Akhter, Javed; Das, Lalu; Deb, Argha

2017-09-01

Performances of the state-of-the-art CMIP5 models in reproducing the spatial rainfall patterns over seven homogeneous rainfall zones of India viz. North Mountainous India (NMI), Northwest India (NWI), North Central India (NCI), Northeast India (NEI), West Peninsular India (WPI), East Peninsular India (EPI) and South Peninsular India (SPI) have been assessed using different conventional performance metrics namely spatial correlation (R), index of agreement (d-index), Nash-Sutcliffe efficiency (NSE), Ratio of RMSE to the standard deviation of the observations (RSR) and mean bias (MB). The results based on these indices revealed that majority of the models are unable to reproduce finer-scaled spatial patterns over most of the zones. Thereafter, four bias correction methods i.e. Scaling, Standardized Reconstruction, Empirical Quantile Mapping and Gamma Quantile Mapping have been applied on GCM simulations to enhance the skills of the GCM projections. It has been found that scaling method compared to other three methods shown its better skill in capturing mean spatial patterns. Multi-model ensemble (MME) comprising 25 numbers of better performing bias corrected (Scaled) GCMs, have been considered for developing future rainfall patterns over seven zones. Models' spread from ensemble mean (uncertainty) has been found to be larger in RCP 8.5 than RCP4.5 ensemble. In general, future rainfall projections from RCP 4.5 and RCP 8.5 revealed an increasing rainfall over seven zones during 2020s, 2050s, and 2080s. The maximum increase has been found over southwestern part of NWI (12-30%), northwestern part of WPI (3-30%), southeastern part of NEI (5-18%) and northern and eastern part of SPI (6-24%). However, the contiguous region comprising by the southeastern part of NCI and northeastern part of EPI, may experience slight decreasing rainfall (about 3%) during 2020s whereas the western part of NMI may also receive around 3% reduction in rainfall during both 2050s and 2080s.

Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains.

PubMed

Nolan, Bernard T; Dubus, Igor G; Surdyk, Nicolas; Fowler, Hayley J; Burton, Aidan; Hollis, John M; Reichenberger, Stefan; Jarvis, Nicholas J

2008-09-01

Key climatic factors influencing the transport of pesticides to drains and to depth were identified. Climatic characteristics such as the timing of rainfall in relation to pesticide application may be more critical than average annual temperature and rainfall. The fate of three pesticides was simulated in nine contrasting soil types for two seasons, five application dates and six synthetic weather data series using the MACRO model, and predicted cumulative pesticide loads were analysed using statistical methods. Classification trees and Pearson correlations indicated that simulated losses in excess of 75th percentile values (0.046 mg m(-2) for leaching, 0.042 mg m(-2) for drainage) generally occurred with large rainfall events following autumn application on clay soils, for both leaching and drainage scenarios. The amount and timing of winter rainfall were important factors, whatever the application period, and these interacted strongly with soil texture and pesticide mobility and persistence. Winter rainfall primarily influenced losses of less mobile and more persistent compounds, while short-term rainfall and temperature controlled leaching of the more mobile pesticides. Numerous climatic characteristics influenced pesticide loss, including the amount of precipitation as well as the timing of rainfall and extreme events in relation to application date. Information regarding the relative influence of the climatic characteristics evaluated here can support the development of a climatic zonation for European-scale risk assessment for pesticide fate.

A further assessment of vegetation feedback on decadal Sahel rainfall variability

NASA Astrophysics Data System (ADS)

Kucharski, Fred; Zeng, Ning; Kalnay, Eugenia

2013-03-01

The effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM ("SPEEDY") is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes. In the control experiment, where the full vegetation feedback is included, the ensemble is consistent with the observed decadal rainfall variability, with a forced component 60 % of the observed variability. In a sensitivity experiment where climatological vegetation cover and albedo are prescribed from the control experiment, the ensemble of simulations is not consistent with the observations because of strongly reduced amplitude of decadal rainfall variability, and the forced component drops to 35 % of the observed variability. The decadal rainfall variability is driven by SST forcing, but significantly enhanced by land-surface feedbacks. Both, local evaporation and moisture flux convergence changes are important for the total rainfall response. Also the internal decadal variability across the ensemble members (not SST-forced) is much stronger in the control experiment compared with the one where vegetation cover and albedo are prescribed. It is further shown that this positive vegetation feedback is physically related to the albedo feedback, supporting the Charney hypothesis.

Convective Cloud and Rainfall Processes Over the Maritime Continent: Simulation and Analysis of the Diurnal Cycle

NASA Astrophysics Data System (ADS)

Gianotti, Rebecca L.

The Maritime Continent experiences strong moist convection, which produces significant rainfall and drives large fluxes of heat and moisture to the upper troposphere. Despite the importance of these processes to global circulations, current predictions of climate change over this region are still highly uncertain, largely due to inadequate representation of the diurnally-varying processes related to convection. In this work, a coupled numerical model of the land-atmosphere system (RegCM3-IBIS) is used to investigate how more physically-realistic representations of these processes can be incorporated into large-scale climate models. In particular, this work improves simulations of convective-radiative feedbacks and the role of cumulus clouds in mediating the diurnal cycle of rainfall. Three key contributions are made to the development of RegCM3-IBIS. Two pieces of work relate directly to the formation and dissipation of convective clouds: a new representation of convective cloud cover, and a new parameterization of convective rainfall production. These formulations only contain parameters that can be directly quantified from observational data, are independent of model user choices such as domain size or resolution, and explicitly account for subgrid variability in cloud water content and nonlinearities in rainfall production. The third key piece of work introduces a new method for representation of cloud formation within the boundary layer. A comprehensive evaluation of the improved model was undertaken using a range of satellite-derived and ground-based datasets, including a new dataset from Singapore's Changi airport that documents diurnal variation of the local boundary layer height. The performance of RegCM3-IBIS with the new formulations is greatly improved across all evaluation metrics, including cloud cover, cloud liquid water, radiative fluxes and rainfall, indicating consistent improvement in physical realism throughout the simulation. This work demonstrates that: (1) moist convection strongly influences the near surface environment by mediating the incoming solar radiation and net radiation at the surface; (2) dissipation of convective cloud via rainfall plays an equally important role in the convectiveradiative feedback as the formation of that cloud; and (3) over parts of the Maritime Continent, rainfall is a product of diurnally-varying convective processes that operate at small spatial scales, on the order of 1 km. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup

2013-04-01

Errors in the forcing data are sometimes overlooked in hydrological studies even when they could be the most important source of uncertainty. The latter particularly holds true in tropical countries with short historical records of rainfall monitoring and remote areas with sparse rain gauge network. In such instances, alternative data such as the remotely sensed precipitation from the TRMM (Tropical Rainfall Measuring Mission) satellite have been used. These provide a good spatial representation of rainfall processes but have been established in the literature to contain volumetric biases that may impair the results of hydrological modelling or worse, are compensated during model calibration. In this study, we analysed precipitation time series from the TMPA (TRMM Multiple Precipitation Algorithm, version 6) against measurements from over 300 gauges in the Andes and Amazon regions of Peru and Ecuador. We found moderately good monthly correlation between the pixel and gauge pairs but a severe underestimation of rainfall amounts and wet days. The discrepancy between the time series pairs is particularly visible over the east side of the Andes and may be attributed to localized and orographic-driven high intensity rainfall, which the satellite product may have limited skills at capturing due to technical and scale issues. This consequently results in a low bias in the simulated streamflow volumes further downstream. In comparison, with the recently released TMPA, version 7, the biases reduce. This work further explores several approaches to merge the two sources of rainfall measurements, each of a different spatial and temporal support, with the objective of improving the representation of rainfall in hydrological simulations. The methods used are (1) mean bias correction (2) data assimilation using Kalman filter Bayesian updating. The results are evaluated by means of (1) a comparison of runoff ratios (the ratio of the total runoff and the total precipitation over an extended period) in multiple basins, and (2) a comparison of the outcome of hydrological modelling using the distributed JULES (Joint-UK Land Environment Simulator) land surface model. First results indicate an improvement in the water balance that directly translates into an increased hydrological performance. The more interesting aspect of the study, however, will be the insights into the nature of satellite precipitation errors in this extreme environment and the optimal means of improving the data to generate increased confidence in hydrological predictions.

A First Approach to Global Runoff Simulation using Satellite Rainfall Estimation

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Hossain, Faisal; Curtis, Scott; Huffman, George J.

2007-01-01

Many hydrological models have been introduced in the hydrological literature to predict runoff but few of these have become common planning or decision-making tools, either because the data requirements are substantial or because the modeling processes are too complicated for operational application. On the other hand, progress in regional or global rainfall-runoff simulation has been constrained by the difficulty of measuring spatiotemporal variability of the primary causative factor, i.e. rainfall fluxes, continuously over space and time. Building on progress in remote sensing technology, researchers have improved the accuracy, coverage, and resolution of rainfall estimates by combining imagery from infrared, passive microwave, and space-borne radar sensors. Motivated by the recent increasing availability of global remote sensing data for estimating precipitation and describing land surface characteristics, this note reports a ballpark assessment of quasi-global runoff computed by incorporating satellite rainfall data and other remote sensing products in a relatively simple rainfall-runoff simulation approach: the Natural Resources Conservation Service (NRCS) runoff Curve Number (CN) method. Using an Antecedent Precipitation Index (API) as a proxy of antecedent moisture conditions, this note estimates time-varying NRCS-CN values determined by the 5-day normalized API. Driven by multi-year (1998-2006) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis, quasi-global runoff was retrospectively simulated with the NRCS-CN method and compared to Global Runoff Data Centre data at global and catchment scales. Results demonstrated the potential for using this simple method when diagnosing runoff values from satellite rainfall for the globe and for medium to large river basins. This work was done with the simple NRCS-CN method as a first-cut approach to understanding the challenges that lie ahead in advancing the satellite-based inference of global runoff. We expect that the successes and limitations revealed in this study will lay the basis for applying more advanced methods to capture the dynamic variability of the global hydrologic process for global runoff monltongin real time. The essential ingredient in this work is the use of global satellite-based rainfall estimation.

Attribution of Extreme Rainfall from Landfalling Tropical Cyclones to Climate Change for the Eastern United States

NASA Astrophysics Data System (ADS)

Liu, M.; Yang, L.; Smith, J. A.; Vecchi, G. A.

2017-12-01

Extreme rainfall and flooding associated with landfalling tropical cyclones (TC) is responsible for vast socioeconomic losses and fatalities. Landfalling tropical cyclones are an important element of extreme rainfall and flood peak distributions in the eastern United States. Record floods for USGS stream gauging stations over the eastern US are closely tied to landfalling hurricanes. A small number of storms account for the largest record floods, most notably Hurricanes Diane (1955) and Agnes (1972). The question we address is: if the synoptic conditions accompanying those hurricanes were to be repeated in the future, how would the thermodynamic and dynamic storm properties and associated extreme rainfall differ in response to climate change? We examine three hurricanes: Diane (1955), Agnes (1972) and Irene (2011), due to the contrasts in structure/evolution properties and their important roles in dictating the upper tail properties of extreme rainfall and flood frequency over eastern US. Extreme rainfall from Diane is more localized as the storm maintains tropical characteristics, while synoptic-scale vertical motion associated with extratropical transition is a central feature for extreme rainfall induced by Agnes. Our analyses are based on ensemble simulations using the Weather Research and Forecasting (WRF) model, considering combinations of different physics options (i.e., microphysics, boundary layer schemes). The initial and boundary conditions of WRF simulations for the present-day climate are using the Twentieth Century Reanalysis (20thCR). A sub-selection of GCMs is used, as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5), to provide future climate projections. For future simulations, changes in model fields (i.e., temperature, humidity, geopotential height) between present-day and future climate are first derived and then added to the same 20thCR initial and boundary data used for the present-day simulations, and the ensemble is rerun using identical model configurations. Response of extreme rainfall as well as changes in thermodynamic and dynamic storm properties will be presented and analyzed. Contrasting responses across the three storm events to climate change will shed light on critical environmental factors for TC-related extreme rainfall over eastern US.

Ensemble flood simulation for a small dam catchment in Japan using 10 and 2 km resolution nonhydrostatic model rainfalls

NASA Astrophysics Data System (ADS)

Kobayashi, Kenichiro; Otsuka, Shigenori; Apip; Saito, Kazuo

2016-08-01

This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.

WegenerNet 1km-scale sub-daily rainfall data and their application: a hydrological modeling study on the sensitivity of small-catchment runoff to spatial rainfall variability

NASA Astrophysics Data System (ADS)

Oh, Sungmin; Hohmann, Clara; Foelsche, Ulrich; Fuchsberger, Jürgen; Rieger, Wolfgang; Kirchengast, Gottfried

2017-04-01

WegenerNet Feldbach region (WEGN), a pioneering experiment for weather and climate observations, has recently completed its first 10-year precipitation measurement cycle. The WEGN has measured precipitation, temperature, humidity, and other parameters since the beginning of 2007, supporting local-level monitoring and modeling studies, over an area of about 20 km x 15 km centered near the City of Feldbach (46.93 ˚ N, 15.90 ˚ E) in the Alpine forelands of southeast Austria. All the 151 stations in the network are now equipped with high-quality Meteoservis sensors as of August 2016, following an equipment with Friedrichs sensors at most stations before, and continue to provide high-resolution (2 km2/5-min) gauge based precipitation measurements for interested users in hydro-meteorological communities. Here we will present overall characteristics of the WEGN, with a focus on sub-daily precipitation measurements, from the data processing (data quality control, gridded data products generation, etc.) to data applications (e.g., ground validation of satellite estimates). The latter includes our recent study on the propagation of uncertainty from rainfall to runoff. The study assesses responses of small-catchment runoff to spatial rainfall variability in the WEGN region over the Raab valley, using a physics-based distributed hydrological model; Water Flow and Balance Simulation Model (WaSiM), developed at ETH Zurich (Schulla, ETH Zurich, 1997). Given that uncertainty due to resolution of rainfall measurements is believed to be a significant source of error in hydrologic modeling especially for convective rainfall that dominates in the region during summer, the high-resolution of WEGN data furnishes a great opportunity to analyze effects of rainfall events on the runoff at different spatial resolutions. Furthermore, the assessment can be conducted not only for the lower Raab catchment (area of about 500 km2) but also for its sub-catchments (areas of about 30-70 km2). Beside the question how many stations are necessary for reliable hydrological modeling, different interpolation methods like Inverse Distance Interpolation, Elevation Dependent Regression, and combinations will be tested. This presentation will show the first results from a scale-depending analysis of spatial and temporal structures of heavy rainfall events and responses of simulated runoff at the event scale in the WEGN region.

Missing pieces of the puzzle: understanding decadal variability of Sahel Rainfall

NASA Astrophysics Data System (ADS)

Vellinga, Michael; Roberts, Malcolm; Vidale, Pier-Luigi; Mizielinski, Matthew; Demory, Marie-Estelle; Schiemann, Reinhard; Strachan, Jane; Bain, Caroline

2015-04-01

The instrumental record shows that substantial decadal fluctuations affected Sahel rainfall from the West African monsoon throughout the 20th century. Climate models generally underestimate the magnitude of decadal Sahel rainfall changes compared to observations. This shows that the processes that control low-frequency Sahel rainfall change are misrepresented in most CMIP5-era climate models. Reliable climate information of future low-frequency rainfall changes thus remains elusive. Here we identify key processes that control the magnitude of the decadal rainfall recovery in the Sahel since the mid-1980s. We show its sensitivity to model resolution and physics in a suite of experiments with global HadGEM3 model configurations at resolutions between 130-25 km. The decadal rainfall trend increases with resolution and at 60-25 km falls within the observed range. Higher resolution models have stronger increases of moisture supply and of African Easterly wave activity. Easterly waves control the occurrence of strong organised rainfall events which carry most of the decadal trend. Weak rainfall events occur too frequently at all resolutions and at low resolution contribute substantially to the decadal trend. All of this behaviour is seen across CMIP5, including future scenarios. Additional simulations with a global 12km version of HadGEM3 show that treating convection explicitly dramatically improves the properties of Sahel rainfall systems. We conclude that interaction between convective scale and global scale processes is key to decadal rainfall changes in the Sahel. This work is distributed under the Creative Commons Attribution 3.0 Unported License together with an author copyright. This license does not conflict with the regulations of the Crown Copyright.Crown Copyright

Ability of WRF to Simulate Rainfall Distribution Over West Africa: Role of Horizontal Resolution and Dynamical Processes

NASA Astrophysics Data System (ADS)

Kouadio, K.; Konare, A.; Bastin, S.; Ajayi, V. O.

2016-12-01

This research work focused on the thorny problem of the representation of rainfall over West Africa and particularly in the Gulf of Guinea and its surroundings by Regional Climate Models (RCMs). The sensitivities of Weather Research and Forecasting (WRF) Model are tested for changes in horizontal resolution (convective permitting versus parameterized) on the replication of West African Climate in year 2014 and also changes in microphysics (MP) and planetary boundary layer (PBL) schemes on June 2014. The sensitivity to horizontal resolution study show that both runs at 24km and 4km (explicit convection) resolution fairly replicate the general distribution of the rainfall over West African region. The analysis also reveals a good replication of the dynamical features of West African monsoon system including Tropical Easterly Jet (TEJ), African Easterly Jet (AEJ), monsoon flow and the West African Heat Low (WAHL). Some differences have been noticed between WRF and ERA-interim outputs irrespective to the spectral nudging used in the experiment which then suggest strong interactions between scales. The link between the seasonal displacement of the WAHL and the spatial distribution of the rainfall and the Sahelian onset is confirmed in this study. The results also show an improvement on the replication of rainfall with the very high resolution run observed at daily scale over the Sahel while a dry bias is observed in WRF simulations of the rainfall over Ivorian Coast and in the Gulf of Guinea. Generally, over the Guinean coast the high resolution run did not provide subsequent improvement on the replication of rainfall. The sensitivity of WRF to MP and PBL on rainfall replication study reveals that the most significant added value over the Guinean coast and surroundings area is provided by the configurations that used the PBL Asymmetric Convective Model V2 (ACM2) suggesting more influence of the PBL compared to MP. The change on microphysics and planetary boundary layer schemes in general, seems to have less effect on the explicit runs into the replication of the rainfall over the Gulf of Guinea and the surroundings seaboard.

Design and hydraulic characteristics of a field-scale bi-phasic bioretention rain garden system for storm water management.

PubMed

Yang, H; Florence, D C; McCoy, E L; Dick, W A; Grewal, P S

2009-01-01

A field-scale bioretention rain garden system was constructed using a novel bi-phasic (i.e. sequence of anaerobic to aerobic) concept for improving retention and removal of storm water runoff pollutants. Hydraulic tests with bromide tracer and simulated runoff pollutants (nitrate-N, phosphate-P, Cu, Pb, and Zn) were performed in the system under a simulated continuous rainfall. The objectives of the tests were (1) to determine hydraulic characteristics of the system, and (2) to evaluate the movement of runoff pollutants through the system. For the 180 mm/24 h rainfall, the bi-phasic bioretention system effectively reduced both peak flow (approximately 70%) and runoff volume (approximately 42%). The breakthrough curves (BTCs) of bromide tracer suggest that the transport pattern of the system is similar to dispersed plug flow under this large runoff event. The BTCs of bromide showed mean 10% and 90% breakthrough times of 5.7 h and 12.5 h, respectively. Under the continuous rainfall, a significantly different transport pattern was found between each runoff pollutant. Nitrate-N was easily transported through the system with potential leaching risk from the initial soil medium, whereas phosphate-P and metals were significantly retained indicating sorption-mediated transport. These findings support the importance of hydraulics, in combination with the soil medium, when creating bioretention systems for bioremediation that are effective for various rainfall sizes and intervals.

Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China)

NASA Astrophysics Data System (ADS)

Li, Dan; Christakos, George; Ding, Xinxin; Wu, Jiaping

2018-01-01

Spatial rainfall data is an essential input to Distributed Hydrological Models (DHM), and a significant contributor to hydrological model uncertainty. Model uncertainty is higher when rain gauges are sparse, as is often the case in practice. Currently, satellite-based precipitation products increasingly provide an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment is required before implementation. Accordingly, the twofold objective of this work paper was the real-world assessment of both (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, and (b) the TRMM product's role in forcing data for hydrologic simulations in the area of the Tiaoxi catchment (Taihu lake basin, China). The TRMM rainfall products used in this study are the Version-7 real-time 3B42RT and the post-real-time 3B42. It was found that the TRMM rainfall data showed a superior performance at the monthly and annual scales, fitting well with surface observation-based frequency rainfall distributions. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) and the relative bias ratio (BIAS) were used to evaluate hydrologic model performance. The satisfactory performance of the monthly runoff simulations in the Tiaoxi study supports the view that the implementation of real-time 3B42RT allows considerable room for improvement. At the same time, post-real-time 3B42 can be a valuable tool of hydrologic modeling, water balance analysis, and basin water resource management, especially in developing countries or at remote locations in which rainfall gauges are scarce.

Assessment of the Effects of Various Precipitation Forcings on Flood Forecasting Potential Using WRF-Hydro Modeling

NASA Astrophysics Data System (ADS)

Zhang, J.; Fang, N. Z.

2017-12-01

A potential flood forecast system is under development for the Upper Trinity River Basin (UTRB) in North Central of Texas using the WRF-Hydro model. The Routing Application for the Parallel Computation of Discharge (RAPID) is utilized as channel routing module to simulate streamflow. Model performance analysis was conducted based on three quantitative precipitation estimates (QPE): the North Land Data Assimilation System (NLDAS) rainfall, the Multi-Radar Multi-Sensor (MRMS) QPE and the National Centers for Environmental Prediction (NCEP) quality-controlled stage IV estimates. Prior to hydrologic simulation, QPE performance is assessed on two time scales (daily and hourly) using the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) and Hydrometeorological Automated Data System (HADS) hourly products. The calibrated WRF-Hydro model was then evaluated by comparing the simulated against the USGS observed using various QPE products. The results imply that the NCEP stage IV estimates have the best accuracy among the three QPEs on both time scales, while the NLDAS rainfall performs poorly because of its coarse spatial resolution. Furthermore, precipitation bias demonstrates pronounced impact on flood forecasting skills, as the root mean squared errors are significantly reduced by replacing NLDAS rainfall with NCEP stage IV estimates. This study also demonstrates that accurate simulated results can be achieved when initial soil moisture values are well understood in the WRF-Hydro model. Future research effort will therefore be invested on incorporating data assimilation with focus on initial states of the soil properties for UTRB.

A field evaluation of a satellite microwave rainfall sensor network

NASA Astrophysics Data System (ADS)

Caridi, Andrea; Caviglia, Daniele D.; Colli, Matteo; Delucchi, Alessandro; Federici, Bianca; Lanza, Luca G.; Pastorino, Matteo; Randazzo, Andrea; Sguerso, Domenico

2017-04-01

An innovative environmental monitoring system - Smart Rainfall System (SRS) - that estimates rainfall in real-time by means of the analysis of the attenuation of satellite signals (DVB-S in the microwave Ku band) is presented. Such a system consists in a set of peripheral microwave sensors placed on the field of interest, and connected to a central processing and analysis node. It has been developed jointly by the University of Genoa, with its departments DITEN and DICCA and the Genoese SME "Darts Engineering Srl". This work discusses the rainfall intensity measurements accuracy and sensitivity performance of SRS, based on preliminary results from a field comparison experiment at the urban scale. The test-bed is composed by a set of preliminary measurement sites established from Autumn 2016 in the Genoa (Italy) municipality and the data collected from the sensors during a selection of rainfall events is studied. The availability of point-scale rainfall intensity measurements made by traditional tipping-bucket rain gauges and radar areal observations allows a comparative analysis of the SRS performance. The calibration of the reference rain gauges has been carried out at the laboratories of DICCA using a rainfall simulator and the measurements have been processed taking advantage of advanced algorithms to reduce counting errors. The experimental set-up allows a fine tuning of the retrieval algorithm and a full characterization of the accuracy of the rainfall intensity estimates from the microwave signal attenuation as a function of different precipitation regimes.

Bare soil erosion modelling with rainfall simulations: experiments on crop and recently burned areas

NASA Astrophysics Data System (ADS)

Catani, F.; Menci, S.; Moretti, S.; Keizer, J.

2006-12-01

The use of numerical models is of fundamental importance in the comprehension and prediction of soil erosion. At the very basis of the calibration process of the numerical models are the direct measurements of the governing parameters, carried out during field or laboratory tests. To measure and model soil erosion rainfall simulations can be used, that allow the reproduction of project rainfall having chosen characteristics of intensity and duration. The main parameters that rainfall simulators can measure are hydraulic conductivity, parameters of soil erodibility, rate and features of splash erosion, discharge coefficient and sediment yield. Other important parameters can be estimated during the rainfall simulations through the use of photogrammetric instruments able to memorize high definition stereographic models of the soil plot under analysis at different time steps. In this research rainfall simulator experiments (rse) were conducted to measure and quantify runoff and erosion processes on selected bare soil plots. The selected plots are located in some vineyards, olive groves and crops in central Italy and in some recently burned areas in north-central Portugal, affected by a wildfire during early July 2005 and, at the time, largely covered by commercial eucalypt plantations. On the Italian crops the choice of the rainfall intensities and durations were performed on the basis of the previous knowledge of the selected test areas. The procedure was based on an initial phase of soil wetting and a following phase of 3 erosion cycles. The first should reproduce the effects of a normal rainfall with a return time of 2 years (23 mm/h). The second should represent a serious episode with a return time of 10 years (34 mm/h). The third has the objective to reproduce and understand the effects of an intense precipitation event, with a return time of 50 years (41 mm/h). During vineyards experiments some photogrammetric surveys were carried out as well. In the Portugal burned areas, to measure the influence of rain intensities, two rainfall simulations have been carried out simultaneously, one with an intensity of 45 mm/h and one with 85 mm/h. In both cases, before the experiments, soil and vegetation cover description have been made and soil samples have been taken. During the simulations soil samples leaving the parcels were taken at suitable time intervals to measure the sediment yield and the runoff. The rse data have been thought to provide a sufficient basis for erosion modelling at the small-plot scale and, through upscaling, for predicting erosion rates at the slope scale. For this purpose two soil erosion models, WEPP and MEFIDIS, have been selected and then compared. The comparison has shown a certain degree of uncertainty in numeric erosion prediction, due to the non linearity of the overland erosion processes, and to technical and conceptual difficulties, including the data collection. In the following laboratory phase high resolution (2 by 2 mm) DEMs of the vineyards plot are being produced for each meaningful processing phase. The digital elevation models will then be analysed to asses calibration parameters such as soil roughness (expressed by standard deviation of elevations, fractal dimension and local relief energy), soil and sediment transfer (hypsometric curves, local elevation and volume differences) and rill network evolution (Horton ordering, stream lengths, contributing area, drainage density, Hack's law)

Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset.

Downscaling of a global climate model for estimation of runoff, sediment yield and dam storage: A case study of Pirapama basin, Brazil

NASA Astrophysics Data System (ADS)

Braga, Ana Cláudia F. Medeiros; Silva, Richarde Marques da; Santos, Celso Augusto Guimarães; Galvão, Carlos de Oliveira; Nobre, Paulo

2013-08-01

The coastal zone of northeastern Brazil is characterized by intense human activities and by large settlements and also experiences high soil losses that can contribute to environmental damage. Therefore, it is necessary to build an integrated modeling-forecasting system for rainfall-runoff erosion that assesses plans for water availability and sediment yield that can be conceived and implemented. In this work, we present an evaluation of an integrated modeling system for a basin located in this region with a relatively low predictability of seasonal rainfall and a small area (600 km2). The National Center for Environmental Predictions - NCEP’s Regional Spectral Model (RSM) nested within the Center for Weather Forecasting and Climate Studies - CPTEC’s Atmospheric General Circulation Model (AGCM) were investigated in this study, and both are addressed in the simulation work. The rainfall analysis shows that: (1) the dynamic downscaling carried out by the regional RSM model approximates the frequency distribution of the daily observed data set although errors were detected in the magnitude and timing (anticipation of peaks, for example) at the daily scale, (2) an unbiased precipitation forecast seemed to be essential for use of the results in hydrological models, and (3) the information directly extracted from the global model may also be useful. The simulated runoff and reservoir-stored volumes are strongly linked to rainfall, and their estimation accuracy was significantly improved at the monthly scale, thus rendering the results useful for management purposes. The runoff-erosion forecasting displayed a large sediment yield that was consistent with the predicted rainfall.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2010-01-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2017-12-01

In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

Temporal sequencing of throughfall drop generation as revealed by use of a large-scale rainfall simulator

NASA Astrophysics Data System (ADS)

Nanko, K.; Levia, D. F., Jr.; Iida, S.; SUN, X.; Shinohara, Y.; Sakai, N.

2017-12-01

Scientists have been interested in throughfall drop size and its distribution because of its importance to soil erosion and the forest water balance. An indoor experiment was employed to deepen our understanding of throughfall drop generation processes to promote better management of forested ecosystems. The indoor experiment provides a unique opportunity to examine an array of constant rainfall intensities that are ideal conditions to pick up the effect of changing intensities and not found in the fields. Throughfall drop generation was examined for three species- Cryptomeria japonica D. Don (Japanese cedar), Chamaecyparis obtusa (Siebold & Zucc.) Endl. (Japanese cypress), and Zelkova serrata Thunb. (Japanese zelkova)- under both leafed and leafless conditions in the large-scale rainfall simulator in the National Research Institute for Earth Science and Disaster Resilience (Tsukuba, Japan) at varying rainfall intensities ranging from15 to 100 mm h-1. Drop size distributions of the applied rainfall and throughfall were measured simultaneously by 20 laser disdrometers. Utilizing the drop size dataset, throughfall was separated into three components: free throughfall, canopy drip, and splash throughfall. The temporal sequencing of the throughfall components were analyzed on a 1-min interval during each experimental run. The throughfall component percentage and drop size of canopy drip differed among tree species and rainfall intensities and by elapsed time from the beginning of the rainfall event. Preliminary analysis revealed that the time differences to produce branch drip as compared to leaf (or needle) drip was partly due to differential canopy wet-up processes and the disappearance of branch drips due to canopy saturation, leading to dissimilar throughfall drop size distributions beneath the various tree species examined. This research was supported by JSPS Invitation Fellowship for Research in Japan (Grant No.: S16088) and JSPS KAKENHI (Grant No.: JP15H05626).

Short-Range Prediction of Monsoon Precipitation by NCMRWF Regional Unified Model with Explicit Convection

NASA Astrophysics Data System (ADS)

Mamgain, Ashu; Rajagopal, E. N.; Mitra, A. K.; Webster, S.

2018-03-01

There are increasing efforts towards the prediction of high-impact weather systems and understanding of related dynamical and physical processes. High-resolution numerical model simulations can be used directly to model the impact at fine-scale details. Improvement in forecast accuracy can help in disaster management planning and execution. National Centre for Medium Range Weather Forecasting (NCMRWF) has implemented high-resolution regional unified modeling system with explicit convection embedded within coarser resolution global model with parameterized convection. The models configurations are based on UK Met Office unified seamless modeling system. Recent land use/land cover data (2012-2013) obtained from Indian Space Research Organisation (ISRO) are also used in model simulations. Results based on short-range forecast of both the global and regional models over India for a month indicate that convection-permitting simulations by the high-resolution regional model is able to reduce the dry bias over southern parts of West Coast and monsoon trough zone with more intense rainfall mainly towards northern parts of monsoon trough zone. Regional model with explicit convection has significantly improved the phase of the diurnal cycle of rainfall as compared to the global model. Results from two monsoon depression cases during study period show substantial improvement in details of rainfall pattern. Many categories in rainfall defined for operational forecast purposes by Indian forecasters are also well represented in case of convection-permitting high-resolution simulations. For the statistics of number of days within a range of rain categories between `No-Rain' and `Heavy Rain', the regional model is outperforming the global model in all the ranges. In the very heavy and extremely heavy categories, the regional simulations show overestimation of rainfall days. Global model with parameterized convection have tendency to overestimate the light rainfall days and underestimate the heavy rain days compared to the observation data.

Temporal nitrous oxide emissions from beef cattle feedlot manure following a simulated rainfall event

USDA-ARS?s Scientific Manuscript database

A pilot-scale, recirculating-flow-through, non-steady-state (RFT-NSS) chamber system was designed for quantifying nitrous oxide (N2O) emissions from simulated open-lot beef cattle feedlot pens. The system employed five 1 square meter steel pans. A lid was placed systematically on each pan and heads...

Modelling runoff on ceramic tile roofs using the kinematic wave equations

NASA Astrophysics Data System (ADS)

Silveira, Alexandre; Abrantes, João; de Lima, João; Lira, Lincoln

2016-04-01

Rainwater harvesting is a water saving alternative strategy that presents many advantages and can provide solutions to address major water resources problems, such as fresh water scarcity, urban stream degradation and flooding. In recent years, these problems have become global challenges, due to climatic change, population growth and increasing urbanisation. Generally, roofs are the first to come into contact with rainwater; thus, they are the best candidates for rainwater harvesting. In this context, the correct evaluation of roof runoff quantity and quality is essential to effectively design rainwater harvesting systems. Despite this, many studies usually focus on the qualitative aspects in detriment of the quantitative aspects. Laboratory studies using rainfall simulators have been widely used to investigate rainfall-runoff processes. These studies enabled a detailed exploration and systematic replication of a large range of hydrologic conditions, such as rainfall spatial and temporal characteristics, providing for a fast way to obtain precise and consistent data that can be used to calibrate and validate numerical models. This study aims to evaluate the performance of a kinematic wave based numerical model in simulating runoff on sloping roofs, by comparing the numerical results with the ones obtained from laboratory rainfall simulations on a real-scale ceramic tile roof (Lusa tiles). For all studied slopes, simulated discharge hydrographs had a good adjust to observed ones. Coefficient of determination and Nash-Sutcliffe efficiency values were close to 1.0. Particularly, peak discharges, times to peak and peak durations were very well simulated.

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

PubMed Central

Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.

2016-01-01

India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

PubMed

Ghosh, Subimal; Vittal, H; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K S; Dhanesh, Y; Sudheer, K P; Gunthe, S S

2016-01-01

India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.

Green roofs'retention performances in different climates

NASA Astrophysics Data System (ADS)

Viola, Francesco; Hellies, Matteo; Deidda, Roberto

2017-04-01

The ongoing process of global urbanization contributes to increasing stormwater runoff from impervious surfaces, threatening also water quality. Green roofs have been proved to be an innovative stormwater management tool to partially restore natural state, enhancing interception, infiltration and evapotranspiration fluxes. The amount of water that is retained within green roofs depends mainly on both soil properties and climate. The evaluation of the retained water is not trivial since it depends on the stochastic soil moisture dynamics. The aim of this work is to explore performances of green roofs, in terms of water retention, as a function of their depth considering different climate regimes. The role of climate in driving water retention has been mainly represented by rainfall and potential evapotranspiration dynamics, which are simulated by a simple conceptual weather generator at daily time scale. The model is able to describe seasonal (in-phase and counter-phase) and stationary behaviors of climatic forcings. Model parameters have been estimated on more than 20,000 historical time series retrieved worldwide. Exemplifying cases are discussed for five different climate scenarios, changing the amplitude and/or the phase of daily mean rainfall and evapotranspiration forcings. The first scenario represents stationary climates, in two other cases the daily mean rainfall or the potential evapotranspiration evolve sinusoidally. In the latter two cases, we simulated the in-phase or in counter-phase conditions. Stochastic forcings have been then used as an input to a simple conceptual hydrological model which simulate soil moisture dynamics, evapotranspiration fluxes, runoff and leakage from soil pack at daily time scale. For several combinations of annual rainfall and potential evapotranspiration, the analysis allowed assessing green roofs' retaining capabilities, at annual time scale. Provided abacus allows a first approximation of possible hydrological benefits deriving from the implementation of intensive or extensive green roofs in different world areas, i.e. less input to sewer systems.

Design and application of a drip-type rainfall simulator adapted to steep topography and low intensity-rainfall characteristics in the Coastal Range of Southern Chile

NASA Astrophysics Data System (ADS)

Mohr, Christian; Anton, Huber

2010-05-01

Besides being adaptable for measuring infiltration, overland flow and sediment transport simultaneously, rainfall simulator systems allow the observation of the processes of runoff generation and soil erosion, too. This enables the assimilation of additional qualitative data and makes a rainfall simulator system a very valid method in the investigation of soil-hydrological response to precipitation events. In the present study a cheap, handy, transportable and easy to set up rainfall simulator applicable for the steep terrain conditions of the Southern Chilean Coastal range was designed based on Bowyer-Bower & Burt (1989). The used drip-type rainfall simulator had to fulfill two main requirements: adaptive to steep topography and little in water consumption. The used simulator is set up by a dismountable rectangular metal rack of 0.5x1.0m basal surface and 2.5m height. The metallic structure enables the attachment of plastic boards for wind protection. Fixable telescopic extensions allow a firm adjustment to slopes up to 45°. Horizontal metallic frames at different heights increase the stability of the structure and carry the devices of the rainfall simulator. On the uppermost frame, two containers provided with calibrated scales spend the water to a fast reacting receptacle assuring constant water supply and pressure by the Mariotte's principle. The rainfall intensity is adjusted by a control-panel according to the Bernoulli principle. This guarantees a constant water flow which was verified by the water-volume leaving the calibrated containers on top. Interchangeable glass-tubes of different diameters in the control-panel permit the generation of various precipitation intensities (4-60 mm/h; SD =0.16mm). The frame beneath carries an acrylic glass box with approx. 600 drop-formers (fishing line inside a 0.76mm Tygon-tube) at its bottom. 20 cm below, a framed 5mm-spacing-mesh serves as a raindrop randomizer. At the base of the simulator sheet metals avoid lateral leakage of overland flow leading the runoff to a cemented trough. The experiments were conducted until a steady state infiltration rate was observed or the runoff ceased. The runoff samples are taken manually in intervals of 5 or 10 min depending on the simulated intensity and amount of runoff. All bottled samples were filtered to determine the sediment concentration. To test the system's effectiveness a pilot-study was conducted in a granitic soil catchment. The obtained values of the infiltration rate indicate that soil physical properties in this area facilitate rapid infiltration and slope did not show main influence. The sediment concentration showed high variability due to heterogeneity of surface and soil characteristics. In a succeeding study 36 rainfall simulations prior to clear-cuts during dry summer-season and rainy winter-season were carried out to determine the effect of both silvicultural practices on micro-scale. Soil hydrological response showed preferential flow patterns and variable infiltration-rates due to topsoil disturbance in the course of previous timber-harvests and differences in soil depth, hydrophobic organic layers and imbedded rocks. Maximum steady state infiltration rates ranged between 7.3 and 32.3 mm/h. In contrast to the expected results, maximum infiltration occurred at steep slopes. Only little sediment transport was measured. Only under high precipitation on steep slopes a moderate sediment transport (0.074 g/l) was documented. Post clear-cut infiltration experiments will be conducted in Jan.-March 2010. Furthermore, a modified tipping-bucket-device will be installed as a runoff collector-device to gain better temporal resolution.

Significant uncertainty in global scale hydrological modeling from precipitation data errors

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

2015-10-01

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.

A Multi-scale Modeling System: Developments, Applications and Critical Issues

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, Jiundar; Atlas, Robert; Randall, David; Lin, Xin; Khairoutdinov, Marat; Li, Jui-Lin; Waliser, Duane E.; Hou, Arthur; Peters-Lidard, Christa;

Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

NASA Astrophysics Data System (ADS)

Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

2015-04-01

Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

Improving a spatial rainfall product using a data-mining approach and its effect on the hydrological response of a meso-scale catchment.

NASA Astrophysics Data System (ADS)

Oriani, F.; Stisen, S.; Demirel, C.

2017-12-01

The spatial representation of rainfall is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the daily grid rainfall product provided by the Danish Meteorological Institute as input to the National Water Resources Model of Denmark. Due to a drastic reduction in the rain gauge network (from approximately 500 stations in the period 1996-2006, to 250 in the period 2007-2014), the grid rainfall product, based on the interpolation of these data, is much less reliable. The research is focused on the Skjern catchment (1,050 km2 western Jutland), where we can dispose of the complete rain-gauge database from the Danish Hydrological Observatory and compute the distributed hydrological response at the 1-km scale.To give a better estimation of the gridded rainfall input, we start from ground measurements by simulating the missing data with a stochastic data-mining approach, then we compute again the grid interpolation. To maximize the predictive power of the technique, combinations of station time-series that are the most informative to each other are selected on the basis of their correlation and available historical data. Then, the missing data inside these time-series are simulated together using the direct sampling technique (DS) [1, 2]. DS simulates a datum by sampling the historical record of the same stations where a similar data pattern occurs, preserving their complex statistical relation. The simulated data are reinjected in the whole dataset and used as well as conditioning data to progressively fill up the gaps in other stations.The results show that the proposed methodology, tested on the period 1995-2012, can increase the realism of the grid rainfall product by regenerating the missing ground measurements. The hydrological response is analyzed considering the observations at 5 hydrological stations. The presented methodology can be used in many regions to regenerate the missing data using the information contained in the historical record and propagate the uncertainty of the prediction to the hydrological response. [1] G.Mariethoz et al. (2010), Water Resour. Res., 10.1029/2008WR007621.[2] F. Oriani et al. (2014), Hydrol. Earth Syst. Sc., 10.5194/hessd-11-3213-2014.

Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleoclimate data

NASA Astrophysics Data System (ADS)

Henley, B. J.; Thyer, M. A.; Kuczera, G. A.

2012-12-01

A hierarchical framework for incorporating modes of climate variability into stochastic simulations of hydrological data is developed, termed the climate-informed multi-time scale stochastic (CIMSS) framework. To characterize long-term variability for the first level of the hierarchy, paleoclimate and instrumental data describing the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO) are analyzed. A new paleo IPO-PDO time series dating back 440 yrs is produced, combining seven IPO-PDO paleo sources using an objective smoothing procedure to fit low-pass filters to individual records. The paleo data analysis indicates that wet/dry IPO-PDO states have a broad range of run-lengths, with 90% between 3 and 33 yr and a mean of 15 yr. Model selection techniques were used to determine a suitable stochastic model to simulate these run-lengths. The Markov chain model, previously used to simulate oscillating wet/dry climate states, was found to underestimate the probability of wet/dry periods >5 yr, and was rejected in favor of a gamma distribution. For the second level of the hierarchy, a seasonal rainfall model is conditioned on the simulated IPO-PDO state. Application to two high-quality rainfall sites close to water supply reservoirs found that mean seasonal rainfall in the IPO-PDO dry state was 15%-28% lower than the wet state. The model was able to replicate observed statistics such as seasonal and multi-year accumulated rainfall distributions and interannual autocorrelations for the case study sites. In comparison, an annual lag-one autoregressive AR(1) model was unable to adequately capture the observed rainfall distribution within separate IPO-PDO states. Furthermore, analysis of the impact of the CIMSS framework on drought risk analysis found that short-term drought risks conditional on IPO/PDO state were considerably higher than the traditional AR(1) model.hort-term conditional water supply drought risks for the CIMSS and AR(1) models for the dry IPO-PDO scenario with a range of initial storage levels expressed as a proportion of the annual demand (yield).

Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

NASA Technical Reports Server (NTRS)

Jin, Menglin; King, Michael D.

2005-01-01

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

Untangling climate signals from autogenic changes in long-term peatland development

NASA Astrophysics Data System (ADS)

Morris, Paul J.; Baird, Andy J.; Young, Dylan M.; Swindles, Graeme T.

2015-12-01

Peatlands represent important archives of Holocene paleoclimatic information. However, autogenic processes may disconnect peatland hydrological behavior from climate and overwrite climatic signals in peat records. We use a simulation model of peatland development driven by a range of Holocene climate reconstructions to investigate climate signal preservation in peat records. Simulated water-table depths and peat decomposition profiles exhibit homeostatic recovery from prescribed changes in rainfall, whereas changes in temperature cause lasting alterations to peatland structure and function. Autogenic ecohydrological feedbacks provide both high- and low-pass filters for climatic information, particularly rainfall. Large-magnitude climatic changes of an intermediate temporal scale (i.e., multidecadal to centennial) are most readily preserved in our simulated peat records. Simulated decomposition signals are offset from the climatic changes that generate them due to a phenomenon known as secondary decomposition. Our study provides the mechanistic foundations for a framework to separate climatic and autogenic signals in peat records.

Difference infiltrometer: a method to measure temporally variable infiltration rates during rainstorms

USGS Publications Warehouse

Moody, John A.; Ebel, Brian A.

2012-01-01

We developed a difference infiltrometer to measure time series of non-steady infiltration rates during rainstorms at the point scale. The infiltrometer uses two, tipping bucket rain gages. One gage measures rainfall onto, and the other measures runoff from, a small circular plot about 0.5-m in diameter. The small size allows the infiltration rate to be computed as the difference of the cumulative rainfall and cumulative runoff without having to route water through a large plot. Difference infiltrometers were deployed in an area burned by the 2010 Fourmile Canyon Fire near Boulder, Colorado, USA, and data were collected during the summer of 2011. The difference infiltrometer demonstrated the capability to capture different magnitudes of infiltration rates and temporal variability associated with convective (high intensity, short duration) and cyclonic (low intensity, long duration) rainstorms. Data from the difference infiltrometer were used to estimate saturated hydraulic conductivity of soil affected by the heat from a wildfire. The difference infiltrometer is portable and can be deployed in rugged, steep terrain and does not require the transport of water, as many rainfall simulators require, because it uses natural rainfall. It can be used to assess infiltration models, determine runoff coefficients, identify rainfall depth or rainfall intensity thresholds to initiate runoff, estimate parameters for infiltration models, and compare remediation treatments on disturbed landscapes. The difference infiltrometer can be linked with other types of soil monitoring equipment in long-term studies for detecting temporal and spatial variability at multiple time scales and in nested designs where it can be linked to hillslope and basin-scale runoff responses.

Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

NASA Astrophysics Data System (ADS)

Garrigues, S.; Olioso, A.; Carrer, D.; Decharme, B.; Calvet, J.-C.; Martin, E.; Moulin, S.; Marloie, O.

2015-10-01

Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations. The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m-2) compared to the negative biases found for SAFRAN (-10 W m-2) and the MSG satellite (-12 W m-2). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by -12 and -16 W m-2, respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The simulation of irrigation by the model provides an accurate irrigation amount over the crop cycle but the timing of irrigation occurrences is frequently unrealistic. Errors in the soil hydrodynamic parameters and the lack of irrigation in the simulation have the largest influence on ET compared to uncertainties in the large-scale climate reanalysis and the LAI climatology. Among climate variables, the errors in yearly ET are mainly related to the errors in yearly rainfall. The underestimation of the available water capacity and the soil hydraulic diffusivity induce a large underestimation of ET over 12 years. The underestimation of radiations by the reanalyses and the absence of irrigation in the simulation lead to the underestimation of ET while the overall overestimation of LAI by the ECOCLIMAP-II climatology induces an overestimation of ET over 12 years. This work shows that the key challenges to monitor the water balance of cropland at regional scale concern the representation of the spatial distribution of the soil hydrodynamic parameters, the variability of the irrigation practices, the seasonal and inter-annual dynamics of vegetation and the spatiotemporal heterogeneity of rainfall.

Influence of rainfall data scarcity on non-point source pollution prediction: Implications for physically based models

NASA Astrophysics Data System (ADS)

Chen, Lei; Xu, Jiajia; Wang, Guobo; Liu, Hongbin; Zhai, Limei; Li, Shuang; Sun, Cheng; Shen, Zhenyao

2018-07-01

Hydrological and non-point source pollution (H/NPS) predictions in ungagged basins have become the key problem for watershed studies, especially for those large-scale catchments. However, few studies have explored the comprehensive impacts of rainfall data scarcity on H/NPS predictions. This study focused on: 1) the effects of rainfall spatial scarcity (by removing 11%-67% of stations based on their locations) on the H/NPS results; and 2) the impacts of rainfall temporal scarcity (10%-60% data scarcity in time series); and 3) the development of a new evaluation method that incorporates information entropy. A case study was undertaken using the Soil and Water Assessment Tool (SWAT) in a typical watershed in China. The results of this study highlighted the importance of critical-site rainfall stations that often showed greater influences and cross-tributary impacts on the H/NPS simulations. Higher missing rates above a certain threshold as well as missing locations during the wet periods resulted in poorer simulation results. Compared to traditional indicators, information entropy could serve as a good substitute because it reflects the distribution of spatial variability and the development of temporal heterogeneity. This paper reports important implications for the application of Distributed Hydrological Models and Semi-distributed Hydrological Models, as well as for the optimal design of rainfall gauges among large basins.

Climate downscaling over South America for 1971-2000: application in SMAP rainfall-runoff model for Grande River Basin

NASA Astrophysics Data System (ADS)

da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio

2018-03-01

This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate model and that data from regional models must be bias-corrected so as to improve their results.

Rainfall-runoff properties of tephra: Simulated effects of grain-size and antecedent rainfall

NASA Astrophysics Data System (ADS)

Jones, Robbie; Thomas, Robert E.; Peakall, Jeff; Manville, Vern

2017-04-01

Rain-triggered lahars (RTLs) are a significant and often persistent secondary volcanic hazard at many volcanoes around the world. Rainfall on unconsolidated volcaniclastic material is the primary initiation mechanism of RTLs: the resultant flows have the potential for large runout distances (> 100 km) and present a substantial hazard to downstream infrastructure and communities. RTLs are frequently anticipated in the aftermath of eruptions, but the pattern, timing and scale of lahars varies on an eruption-by-eruption and even catchment-by-catchment basis. This variability is driven by a set of local factors including the grain size distribution, thickness, stratigraphy and spatial distribution of source material in addition to topography, vegetation coverage and rainfall conditions. These factors are often qualitatively discussed in RTL studies based on post-eruption lahar observations or instrumental detections. Conversely, this study aims to move towards a quantitative assessment of RTL hazard in order to facilitate RTL predictions and forecasts based on constrained rainfall, grain size distribution and isopach data. Calibrated simulated rainfall and laboratory-constructed tephra beds are used within a repeatable experimental set-up to isolate the effects of individual parameters and to examine runoff and infiltration processes from analogous RTL source conditions. Laboratory experiments show that increased antecedent rainfall and finer-grained surface tephra individually increase runoff rates and decrease runoff lag times, while a combination of these factors produces a compound effect. These impacts are driven by increased residual moisture content and decreased permeability due to surface sealing, and have previously been inferred from downstream observations of lahars but not identified at source. Water and sediment transport mechanisms differ based on surface grain size distribution: a fine-grained surface layer displayed airborne remobilisation, accretionary pellet formation, rapid surface sealing and infiltration-excess overland flow generation whilst a coarse surface layer demonstrated exclusively rainsplash-driven particle detachment throughout the rainfall simulations. This experimental protocol has the potential to quantitatively examine the effects of a variety of individual parameters in RTL initiation under controlled conditions.

Effects of recharge, Upper Floridan aquifer heads, and time scale on simulated ground-water exchange with Lake Starr, a seepage lake in central Florida

USGS Publications Warehouse

Swancar, Amy; Lee, Terrie Mackin

2003-01-01

Lake Starr and other lakes in the mantled karst terrain of Florida's Central Lake District are surrounded by a conductive surficial aquifer system that receives highly variable recharge from rainfall. In addition, downward leakage from these lakes varies as heads in the underlying Upper Floridan aquifer change seasonally and with pumpage. A saturated three-dimensional finite-difference ground-water flow model was used to simulate the effects of recharge, Upper Floridan aquifer heads, and model time scale on ground-water exchange with Lake Starr. The lake was simulated as an active part of the model using high hydraulic conductivity cells. Simulated ground-water flow was compared to net ground-water flow estimated from a rigorously derived water budget for the 2-year period August 1996-July 1998. Calibrating saturated ground-water flow models with monthly stress periods to a monthly lake water budget will result in underpredicting gross inflow to, and leakage from, ridge lakes in Florida. Underprediction of ground-water inflow occurs because recharge stresses and ground-water flow responses during rainy periods are averaged over too long a time period using monthly stress periods. When inflow is underestimated during calibration, leakage also is underestimated because inflow and leakage are correlated if lake stage is maintained over the long term. Underpredicted leakage reduces the implied effect of ground-water withdrawals from the Upper Floridan aquifer on the lake. Calibrating the weekly simulation required accounting for transient responses in the water table near the lake that generated the greater range of net ground-water flow values seen in the weekly water budget. Calibrating to the weekly lake water budget also required increasing the value of annual recharge in the nearshore region well above the initial estimate of 35 percent of the rainfall, and increasing the hydraulic conductivity of the deposits around and beneath the lake. To simulate the total ground-water inflow to lakes, saturated-flow models of lake basins need to account for the potential effects of rapid and efficient recharge in the surficial aquifer system closest to the lake. In this part of the basin, the ability to accurately estimate recharge is crucial because the water table is shallowest and the response time between rainfall and recharge is shortest. Use of the one-dimensional LEACHM model to simulate the effects of the unsaturated zone on the timing and magnitude of recharge in the nearshore improved the simulation of peak values of ground-water inflow to Lake Starr. Results of weekly simulations suggest that weekly recharge can approach the majority of weekly rainfall on the nearshore part of the lake basin. However, even though a weekly simulation with higher recharge in the nearshore was able to reproduce the extremes of ground-water exchange with the lake more accurately, it was not consistently better at predicting net ground-water flow within the water budget error than a simulation with lower recharge. The more subtle effects of rainfall and recharge on ground-water inflow to the lake were more difficult to simulate. The use of variably saturated flow modeling, with time scales that are shorter than weekly and finer spatial discretization, is probably necessary to understand these processes. The basin-wide model of Lake Starr had difficulty simulating the full spectrum of ground-water inflows observed in the water budget because of insufficient information about recharge to ground water, and because of practical limits on spatial and temporal discretization in a model at this scale. In contrast, the saturated flow model appeared to successfully simulate the effects of heads in the Upper Floridan aquifer on water levels and ground-water exchange with the lake at both weekly and monthly stress periods. Most of the variability in lake leakage can be explained by the average vertical head difference between the lake and a re

Signature of present and projected climate change at an urban scale: The case of Addis Ababa

NASA Astrophysics Data System (ADS)

Arsiso, Bisrat Kifle; Mengistu Tsidu, Gizaw; Stoffberg, Gerrit Hendrik

2018-06-01

Understanding climate change and variability at an urban scale is essential for water resource management, land use planning, development of adaption plans, mitigation of air and water pollution. However, there are serious challenges to meet these goals due to unavailability of observed and/or simulated high resolution spatial and temporal climate data. The statistical downscaling of general circulation climate model, for instance, is usually driven by sparse observational data hindering the use of downscaled data to investigate urban scale climate variability and change in the past. Recently, these challenges are partly resolved by concerted international effort to produce global and high spatial resolution climate data. In this study, the 1 km2 high resolution NIMR-HadGEM2-AO simulations for future projections under Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios and gridded observations provided by Worldclim data center are used to assess changes in rainfall, minimum and maximum temperature expected under the two scenarios over Addis Ababa city. The gridded 1 km2 observational data set for the base period (1950-2000) is compared to observation from a meteorological station in the city in order to assess its quality for use as a reference (baseline) data. The comparison revealed that the data set has a very good quality. The rainfall anomalies under RCPs scenarios are wet in the 2030s (2020-2039), 2050s (2040-2069) and 2080s (2070-2099). Both minimum and maximum temperature anomalies under RCPs are successively getting warmer during these periods. Thus, the projected changes under RCPs scenarios show a general increase in rainfall and temperatures with strong variabilities in rainfall during rainy season implying level of difficulty in water resource use and management as well as land use planning and management.

Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2

NASA Astrophysics Data System (ADS)

Abhilash, S.; Sahai, A. K.; Borah, N.; Chattopadhyay, R.; Joseph, S.; Sharmila, S.; De, S.; Goswami, B. N.; Kumar, Arun

2014-05-01

An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001-2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.

Radar-driven High-resolution Hydrometeorological Forecasts of the 26 September 2007 Venice flash flood

NASA Astrophysics Data System (ADS)

Massimo Rossa, Andrea; Laudanna Del Guerra, Franco; Borga, Marco; Zanon, Francesco; Settin, Tommaso; Leuenberger, Daniel

2010-05-01

Space and time scales of flash floods are such that flash flood forecasting and warning systems depend upon the accurate real-time provision of rainfall information, high-resolution numerical weather prediction (NWP) forecasts and the use of hydrological models. Currently available high-resolution NWP model models can potentially provide warning forecasters information on the future evolution of storms and their internal structure, thereby increasing convective-scale warning lead times. However, it is essential that the model be started with a very accurate representation of on-going convection, which calls for assimilation of high-resolution rainfall data. This study aims to assess the feasibility of using carefully checked radar-derived quantitative precipitation estimates (QPE) for assimilation into NWP and hydrological models. The hydrometeorological modeling chain includes the convection-permitting NWP model COSMO-2 and a hydrologic-hydraulic models built upon the concept of geomorphological transport. Radar rainfall observations are assimilated into the NWP model via the latent heat nudging method. The study is focused on 26 September 2007 extreme flash flood event which impacted the coastal area of north-eastern Italy around Venice. The hydro-meteorological modeling system is implemented over the Dese river, a 90 km2 catchment flowing to the Venice lagoon. The radar rainfall observations are carefully checked for artifacts, including beam attenuation, by means of physics-based correction procedures and comparison with a dense network of raingauges. The impact of the radar QPE in the assimilation cycle of the NWP model is very significant, in that the main individual organized convective systems were successfully introduced into the model state, both in terms of timing and localization. Also, incorrectly localized precipitation in the model reference run without rainfall assimilation was correctly reduced to about the observed levels. On the other hand, the highest rainfall intensities were underestimated by 20% at a scale of 1000 km2, and the local peaks by 50%. The positive impact of the assimilated radar rainfall was carried over into the free forecast for about 2-5 hours, depending on when this forecast was started, and was larger, when the main mesoscale convective system was present in the initial conditions. The improvements of the meteorological model simulations were directly propagated to the river flow simulations, with an extension of the warning lead time up to three hours.

Effective control parameters in a deep convection scheme for improved simulation of the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Choi, Jin-Ho; Seo, Kyong-Hwan

2017-06-01

This work seeks to find the most effective parameters in a deep convection scheme (relaxed Arakawa-Schubert scheme) of the National Centers of Environmental Prediction Climate Forecast System model for improved simulation of the Madden-Julian Oscillation (MJO). A suite of sensitivity experiments are performed by changing physical components such as the relaxation parameter of mass flux for adjustment of the environment, the evaporation rate from large-scale precipitation, the moisture trigger threshold using relative humidity of the boundary layer, and the fraction of re-evaporation of convective (subgrid-scale) rainfall. Among them, the last two parameters are found to produce a significant improvement. Increasing the strength of these two parameters reduces light rainfall that inhibits complete formation of the tropical convective system or supplies more moisture that help increase a potential energy to large-scale environment in the lower troposphere (especially at 700 hPa), leading to moisture preconditioning favorable for further development and eastward propagation of the MJO. In a more humid environment, more organized MJO structure (i.e., space-time spectral signal, eastward propagation, and tilted vertical structure) is produced.

Land-Climate Feedbacks in Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Asharaf, Shakeel; Ahrens, Bodo

2016-04-01

In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.

Using the raindrop size distribution to quantify the soil detachment rate at the laboratory scale

NASA Astrophysics Data System (ADS)

Jomaa, S.; Jaffrain, J.; Barry, D. A.; Berne, A.; Sander, G. C.

2010-05-01

Rainfall simulators are beneficial tools for studying soil erosion processes and sediment transport for different circumstances and scales. They are useful to better understand soil erosion mechanisms and, therefore, to develop and validate process-based erosion models. Simulators permit experimental replicates for both simple and complex configurations. The 2 m × 6 m EPFL erosion flume is equipped with a hydraulic slope control and a sprinkling system located on oscillating bars 3 m above the surface. It provides a near-uniform spatial rainfall distribution. The intensity of the precipitation can be adjusted by changing the oscillation interval. The flume is filled to a depth of 0.32 m with an agricultural loamy soil. Raindrop detachment is an important process in interrill erosion, the latter varying with the soil properties as well as the raindrop size distribution and drop velocity. Since the soil detachment varies with the kinetic energy of raindrops, an accurate characterization of drop size distribution (DSD, measured, e.g., using a laser disdrometer) can potentially support erosion calculations. Here, a laser disdrometer was used at different rainfall intensities in the EPFL flume to quantify the rainfall event in terms of number of drops, diameter and velocity. At the same time, soil particle motion was measured locally using splash cups. These cups measured the detached material rates into upslope and downslope compartments. In contrast to previously reported splash cup experiments, the cups used in this study were equipped at the top with upside-down funnels, the upper part having the same diameter as the soil sampled at the bottom. This ensured that the soil detached and captured by the device was not re-exposed to rainfall. The experimental data were used to quantify the relationship between the raindrop distribution and the splash-driven sediment transport.

Quantitative Assessment on Anthropogenic Contributions to the Rainfall Extremes Associated with Typhoon Morakot (2009)

NASA Astrophysics Data System (ADS)

Chen, C. T.; Lo, S. H.; Wang, C. C.; Tsuboki, K.

2017-12-01

More than 2000 mm rainfall occurred over southern Taiwan when a category 1 Typhoon Morakot pass through Taiwan in early August 2009. Entire village and hundred of people were buried by massive mudslides induced by record-breaking precipitation. Whether the past anthropogenic warming played a significant role in such extreme event remained very controversial. On one hand, people argue it's nearly impossible to attribute an individual extreme event to global warming. On the other hand, the increase of heavy rainfall is consistent with the expected effects of climate change on tropical cyclone. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall associated with Typhoon Morakot, we adapt an existing probabilistic event attribution framework to simulate a `world that was' and compare it with an alternative condition, 'world that might have been' that removed the historical anthropogenic drivers of climate. One limitation for applying such approach to high-impact weather system is that it will require models capable of capturing the essential processes lead to the studied extremes. Using a cloud system resolving model that can properly simulate the complicated interactions between tropical cyclone, large-scale background, topography, we first perform the ensemble `world that was' simulations using high resolution ECMWF YOTC analysis. We then re-simulate, having adjusted the analysis to `world that might have been conditions' by removing the regional atmospheric and oceanic forcing due to human influences estimated from the CMIP5 model ensemble mean conditions between all forcing and natural forcing only historical runs. Thus our findings are highly conditional on the driving analysis and adjustments therein, but the setup allows us to elucidate possible contribution of anthropogenic forcing to changes in the likelihood of heavy rainfall associated Typhoon Morakot in early August 2009.

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

DOE PAGES

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark; ...

2016-06-21

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

LABORATORY-SCALE SIMULATION OF RUNOFF RESPONSE FROM PERVIOUS-IMPERVIOUS SYSTEMS

EPA Science Inventory

Urban development yields landscapes that are composites of impervious and pervious areas, with a consequent reduction in infiltration and increase in stormwater runoff. Although basic rainfall-runoff models are used in the vast majority of runoff prediction in urban landscapes, t...

Conditional flood frequency and catchment state: a simulation approach

NASA Astrophysics Data System (ADS)

Brettschneider, Marco; Bourgin, François; Merz, Bruno; Andreassian, Vazken; Blaquiere, Simon

2017-04-01

Catchments have memory and the conditional flood frequency distribution for a time period ahead can be seen as non-stationary: it varies with the catchment state and climatic factors. From a risk management perspective, understanding the link of conditional flood frequency to catchment state is a key to anticipate potential periods of higher flood risk. Here, we adopt a simulation approach to explore the link between flood frequency obtained by continuous rainfall-runoff simulation and the initial state of the catchment. The simulation chain is based on i) a three state rainfall generator applied at the catchment scale, whose parameters are estimated for each month, and ii) the GR4J lumped rainfall-runoff model, whose parameters are calibrated with all available data. For each month, a large number of stochastic realizations of the continuous rainfall generator for the next 12 months are used as inputs for the GR4J model in order to obtain a large number of stochastic realizations for the next 12 months. This process is then repeated for 50 different initial states of the soil moisture reservoir of the GR4J model and for all the catchments. Thus, 50 different conditional flood frequency curves are obtained for the 50 different initial catchment states. We will present an analysis of the link between the catchment states, the period of the year and the strength of the conditioning of the flood frequency compared to the unconditional flood frequency. A large sample of diverse catchments in France will be used.

A Quantitative Analysis of the Effects of Human Activities and Climate Change on Rainfall-Runoff in Xiaoqing River Basin

NASA Astrophysics Data System (ADS)

Yang, Y.; Cao, S.; Liu, C.; Liu, Y.

2017-12-01

It is a hot topic to study the effects of human activities on the rainfall-runoff relationship and quantitatively analyze the influencing factors. According to the flexibility of Copula function to capture multivariate interdependent structure, the Copula structure between rainfall and runoff was analyzed by using the rainfall-runoff variation test method based on Archimedean Copula function to diagnose the variation of rainfall-runoff relationship. The correlation of rainfall-runoff relationship could be directly analyzed by Copula function, which could intuitively display the change of runoff in the same rainfall before and after the mutation period. The statistical method was used to simulate the underlying surface conditions before the abrupt point, and the effects of climate change and human activities on runoff changes were calculated. It can finally figure out the effects of human activities on the rainfall-runoff relationship. Taking xiaoqing river for example, the results showed that the rainfall-runoff relationship in the Xiaoqing River Basin variated in 1996 mainly due to the continuous increase of water consumption in the watershed and the change of the runoff attenuation caused by the large-scale water conservancy projects. And interannual or annual change of rainfall was not obvious; compared with the year before the variation , the runoff capacity of the basin was weakened under the same rainfall conditions after the variation ; Rainfall and runoff distribution were significantly changed and the same magnitude of rainfall and probability of runoff change were significantly different in different periods; The statistical method was used to simulate the runoff from 1996 to 2016. Compared with that from 1960 to 1995, the result showed that the contribution rate of human activities to runoff reduction was 46.8% and that of climate change was 53.2%. By relevant reference, rainfall-runoff correlation and analysis of human activities, the result was verified to be reasonable. The study can be applied to other watersheds, or used to diagnose the variation of the relationship between meteorological elements and hydrological elements so as to provide scientific basis for rational exploitation and utilization of river water resources, as well as soil and water conservation.

Summer rainfall over the southwestern Tibetan Plateau controlled by deep convection over the Indian subcontinent

PubMed Central

Dong, Wenhao; Lin, Yanluan; Wright, Jonathon S.; Ming, Yi; Xie, Yuanyu; Wang, Bin; Luo, Yong; Huang, Wenyu; Huang, Jianbin; Wang, Lei; Tian, Lide; Peng, Yiran; Xu, Fanghua

2016-01-01

Despite the importance of precipitation and moisture transport over the Tibetan Plateau for glacier mass balance, river runoff and local ecology, changes in these quantities remain highly uncertain and poorly understood. Here we use observational data and model simulations to explore the close relationship between summer rainfall variability over the southwestern Tibetan Plateau (SWTP) and that over central-eastern India (CEI), which exists despite the separation of these two regions by the Himalayas. We show that this relationship is maintained primarily by ‘up-and-over' moisture transport, in which hydrometeors and moisture are lifted by convective storms over CEI and the Himalayan foothills and then swept over the SWTP by the mid-tropospheric circulation, rather than by upslope flow over the Himalayas. Sensitivity simulations confirm the importance of up-and-over transport at event scales, and an objective storm classification indicates that this pathway accounts for approximately half of total summer rainfall over the SWTP. PMID:26948491

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

NASA Astrophysics Data System (ADS)

Or, D.; von Ruette, J.; Lehmann, P.

2017-12-01

Landslides and subsequent debris-flows initiated by rainfall represent a common natural hazard in mountainous regions. We integrated a landslide hydro-mechanical triggering model with a simple model for debris flow runout pathways and developed a graphical user interface (GUI) to represent these natural hazards at catchment scale at any location. The STEP-TRAMM GUI provides process-based estimates of the initiation locations and sizes of landslides patterns based on digital elevation models (SRTM) linked with high resolution global soil maps (SoilGrids 250 m resolution) and satellite based information on rainfall statistics for the selected region. In the preprocessing phase the STEP-TRAMM model estimates soil depth distribution to supplement other soil information for delineating key hydrological and mechanical properties relevant to representing local soil failure. We will illustrate this publicly available GUI and modeling platform to simulate effects of deforestation on landslide hazards in several regions and compare model outcome with satellite based information.

Effects of rainfall seasonality and soil moisture capacity on mean annual water balance for Australian catchments

USGS Publications Warehouse

Potter, N.J.; Zhang, L.; Milly, P.C.D.; McMahon, T.A.; Jakeman, A.J.

2005-01-01

An important factor controlling catchment‐scale water balance is the seasonal variation of climate. The aim of this study is to investigate the effect of the seasonal distributions of water and energy, and their interactions with the soil moisture store, on mean annual water balance in Australia at catchment scales using a stochastic model of soil moisture balance with seasonally varying forcing. The rainfall regime at 262 catchments around Australia was modeled as a Poisson process with the mean storm arrival rate and the mean storm depth varying throughout the year as cosine curves with annual periods. The soil moisture dynamics were represented by use of a single, finite water store having infinite infiltration capacity, and the potential evapotranspiration rate was modeled as an annual cosine curve. The mean annual water budget was calculated numerically using a Monte Carlo simulation. The model predicted that for a given level of climatic aridity the ratio of mean annual evapotranspiration to rainfall was larger where the potential evapotranspiration and rainfall were in phase, that is, in summer‐dominant rainfall catchments, than where they were out of phase. The observed mean annual evapotranspiration ratios have opposite results. As a result, estimates of mean annual evapotranspiration from the model compared poorly with observational data. Because the inclusion of seasonally varying forcing alone was not sufficient to explain variability in the mean annual water balance, other catchment properties may play a role. Further analysis showed that the water balance was highly sensitive to the catchment‐scale soil moisture capacity. Calibrations of this parameter indicated that infiltration‐excess runoff might be an important process, especially for the summer‐dominant rainfall catchments; most similar studies have shown that modeling of infiltration‐excess runoff is not required at the mean annual timescale.

Simulating transport of nitrogen and phosphorus in a Cambisol after natural and simulated intense rainfall.

PubMed

Kaufmann, Vander; Pinheiro, Adilson; Castro, Nilza Maria dos Reis

2014-05-01

Intense rainfall adversely affects agricultural areas, causing transport of pollutants. Physically-based hydrological models to simulate flows of water and chemical substances can be used to help decision-makers adopt measures which reduce such problems. The purpose of this paper is to evaluate the performance of SWAP and ANIMO models for simulating transport of water, nitrate and phosphorus nutrients, during intense rainfall events generated by a simulator, and during natural rainfall, on a volumetric drainage lysimeter. The models were calibrated and verified using daily time series and simulated rainfall measured at 10-minute intervals. For daily time-intervals, the Nash-Sutcliffe coefficient was 0.865 for the calibration period and 0.805 for verification. Under simulated rainfall, these coefficients were greater than 0.56. The pattern of both nitrate and phosphate concentrations in daily drainage flow under simulated rainfall was acceptably reproduced by the ANIMO model. In the simulated rainfall, loads of nitrate transported in surface runoff varied between 0.08 and 8.46 kg ha(-1), and in drainage form the lysimeter, between 2.44 and 112.57 kg ha(-1). In the case of phosphate, the loads transported in surface runoff varied between 0.002 and 0.504 kg ha(-1), and in drainage, between 0.005 and 1.107 kg ha(-1). The use of the two models SWAP and ANIMO shows the magnitudes of nitrogen and phosphorus fluxes transported by natural and simulated intense rainfall in an agricultural area with different soil management procedures, as required by decision makers. Copyright © 2014 Elsevier B.V. All rights reserved.

Effect of Erosion on Productivity in Subtropical Red Soil Hilly Region: A Multi-Scale Spatio-Temporal Study by Simulated Rainfall

PubMed Central

Li, Zhongwu; Huang, Jinquan; Zeng, Guangming; Nie, Xiaodong; Ma, Wenming; Yu, Wei; Guo, Wang; Zhang, Jiachao

2013-01-01

The effects of water erosion (including long-term historical erosion and single erosion event) on soil properties and productivity in different farming systems were investigated. A typical sloping cropland with homogeneous soil properties was designed in 2009 and then protected from other external disturbances except natural water erosion. In 2012, this cropland was divided in three equally sized blocks. Three treatments were performed on these blocks with different simulated rainfall intensities and farming methods: (1) high rainfall intensity (1.5 - 1.7 mm min−1), no-tillage operation; (2) low rainfall intensity (0.5 - 0.7 mm min−1), no-tillage operation; and (3) low rainfall intensity, tillage operation. All of the blocks were divided in five equally sized subplots along the slope to characterize the three-year effects of historical erosion quantitatively. Redundancy analysis showed that the effects of long-term historical erosion significantly caused most of the variations in soil productivity in no-tillage and low rainfall erosion intensity systems. The intensities of the simulated rainfall did not exhibit significant effects on soil productivity in no-tillage systems. By contrast, different farming operations induced a statistical difference in soil productivity at the same single erosion intensity. Soil organic carbon (SOC) was the major limiting variable that influenced soil productivity. Most explanations of long-term historical erosion for the variation in soil productivity arose from its sharing with SOC. SOC, total nitrogen, and total phosphorus were found as the regressors of soil productivity because of tillage operation. In general, this study provided strong evidence that single erosion event could also impose significant constraints on soil productivity by integrating with tillage operation, although single erosion is not the dominant effect relative to the long-term historical erosion. Our study demonstrated that an effective management of organic carbon pool should be the preferred option to maintain soil productivity in subtropical red soil hilly region. PMID:24147090

A Multiplicative Cascade Model for High-Resolution Space-Time Downscaling of Rainfall

NASA Astrophysics Data System (ADS)

Raut, Bhupendra A.; Seed, Alan W.; Reeder, Michael J.; Jakob, Christian

2018-02-01

Distributions of rainfall with the time and space resolutions of minutes and kilometers, respectively, are often needed to drive the hydrological models used in a range of engineering, environmental, and urban design applications. The work described here is the first step in constructing a model capable of downscaling rainfall to scales of minutes and kilometers from time and space resolutions of several hours and a hundred kilometers. A multiplicative random cascade model known as the Short-Term Ensemble Prediction System is run with parameters from the radar observations at Melbourne (Australia). The orographic effects are added through multiplicative correction factor after the model is run. In the first set of model calculations, 112 significant rain events over Melbourne are simulated 100 times. Because of the stochastic nature of the cascade model, the simulations represent 100 possible realizations of the same rain event. The cascade model produces realistic spatial and temporal patterns of rainfall at 6 min and 1 km resolution (the resolution of the radar data), the statistical properties of which are in close agreement with observation. In the second set of calculations, the cascade model is run continuously for all days from January 2008 to August 2015 and the rainfall accumulations are compared at 12 locations in the greater Melbourne area. The statistical properties of the observations lie with envelope of the 100 ensemble members. The model successfully reproduces the frequency distribution of the 6 min rainfall intensities, storm durations, interarrival times, and autocorrelation function.

A Coupled Approach with Stochastic Rainfall-Runoff Simulation and Hydraulic Modeling for Extreme Flood Estimation on Large Watersheds

NASA Astrophysics Data System (ADS)

Paquet, E.

2015-12-01

The SCHADEX method aims at estimating the distribution of peak and daily discharges up to extreme quantiles. It couples a precipitation probabilistic model based on weather patterns, with a stochastic rainfall-runoff simulation process using a conceptual lumped model. It allows exploring an exhaustive set of hydrological conditions and watershed responses to intense rainfall events. Since 2006, it has been widely applied in France to about one hundred watersheds for dam spillway design, and also aboard (Norway, Canada and central Europe among others). However, its application to large watersheds (above 10 000 km²) faces some significant issues: spatial heterogeneity of rainfall and hydrological processes and flood peak damping due to hydraulic effects (flood plains, natural or man-made embankment) being the more important. This led to the development of an extreme flood simulation framework for large and heterogeneous watersheds, based on the SCHADEX method. Its main features are: Division of the large (or main) watershed into several smaller sub-watersheds, where the spatial homogeneity of the hydro-meteorological processes can reasonably be assumed, and where the hydraulic effects can be neglected. Identification of pilot watersheds where discharge data are available, thus where rainfall-runoff models can be calibrated. They will be parameters donors to non-gauged watersheds. Spatially coherent stochastic simulations for all the sub-watersheds at the daily time step. Identification of a selection of simulated events for a given return period (according to the distribution of runoff volumes at the scale of the main watershed). Generation of the complete hourly hydrographs at each of the sub-watersheds outlets. Routing to the main outlet with hydraulic 1D or 2D models. The presentation will be illustrated with the case-study of the Isère watershed (9981 km), a French snow-driven watershed. The main novelties of this method will be underlined, as well as its perspectives and future improvements.

Rainfall-triggered shallow landslides at catchment scale: Threshold mechanics-based modeling for abruptness and localization

NASA Astrophysics Data System (ADS)

von Ruette, J.; Lehmann, P.; Or, D.

2013-10-01

Rainfall-induced shallow landslides may occur abruptly without distinct precursors and could span a wide range of soil mass released during a triggering event. We present a rainfall-induced landslide-triggering model for steep catchments with surfaces represented as an assembly of hydrologically and mechanically interconnected soil columns. The abruptness of failure was captured by defining local strength thresholds for mechanical bonds linking soil and bedrock and adjacent columns, whereby a failure of a single bond may initiate a chain reaction of subsequent failures, culminating in local mass release (a landslide). The catchment-scale hydromechanical landslide-triggering model (CHLT) was applied to results from two event-based landslide inventories triggered by two rainfall events in 2002 and 2005 in two nearby catchments located in the Prealps in Switzerland. Rainfall radar data, surface elevation and vegetation maps, and a soil production model for soil depth distribution were used for hydromechanical modeling of failure patterns for the two rainfall events at spatial and temporal resolutions of 2.5 m and 0.02 h, respectively. The CHLT model enabled systematic evaluation of the effects of soil type, mechanical reinforcement (soil cohesion and lateral root strength), and initial soil water content on landslide characteristics. We compared various landslide metrics and spatial distribution of simulated landslides in subcatchments with observed inventory data. Model parameters were optimized for the short but intense rainfall event in 2002, and the calibrated model was then applied for the 2005 rainfall, yielding reasonable predictions of landslide events and volumes and statistically reproducing localized landslide patterns similar to inventory data. The model provides a means for identifying local hot spots and offers insights into the dynamics of locally resolved landslide hazards in mountainous regions.

Spatial structure and scaling of macropores in hydrological process at small catchment scale

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter

2013-04-01

During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.

Influence of Madden-Julian Oscillation (MJO) on Rainfall Variability over West Africa at Intraseasonal Timescale

NASA Astrophysics Data System (ADS)

Niang, C.

2015-12-01

Intraseasonal variability of rainfall over West Africa plays a significant role in the economy of the region and is highly linked to agriculture and water resources. This research study aims to investigate the relationship between Madden Julian Oscillation (MJO) and rainfall over West Africa during the boreal summer in the the state-of-the-art Atmospheric Model Intercomparison Project (AMIP) type simulations performed by Atmosphere General Circulation Models (GCMs) forced with prescribed Sea Surface Temperature (SST). It aims to determine the impact of MJO on rainfall and convection over West Africa and identify the dynamical processes which are involved in the state-of-the-art climate simulations. The simulations show in general good skills in capturing its main characteristics as well as its influence on rainfall over West Africa. On the global scale, most models simulated an eastward spatio-temporal propagation of enhanced and suppressed convection similar to the observed. However, over West Africa the MJO signal is weak in few of the models although there is a good coherence in the eastward propagation. The influence on rainfall is well captured in both Sahel and Guinea regions thereby adequately producing the transition between positive and negative rainfall anomalies through the different phases as seen in the observation. Furthermore, the results show that strong active convective phase is clearly associated with the African Easterly Jet (AEJ) but the weak convective phase is associated with a much weaker AEJ particularly over coastal Ghana. In assessing the mechanisms which are involved in the above impacts the convectively equatorial coupled waves (CCEW) are analysed separately. The analysis of the longitudinal propagation of zonal wind at 850hPa and outgoing longwave radiation (OLR) shows that the CCEW are very weak and their extention are very limited beyong West African region. It was found that the westward coupled equatorial Rossby waves are needed to bring out the MJO-convection link over the region and this relationship is well reproduced by all the models. Results also confirmed that it may be possible to predict the anomalous convection over West Africa with a time lead of 15-20 day with regard to Indian Ocean and AMIP simulations performed well in this regard.

Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

NASA Astrophysics Data System (ADS)

Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

2017-04-01

In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a-priori information (topography, lithology, …) and rainfall metrics available from meteorological forecast may allow to better anticipate and mitigates landsliding associated with extreme rainfall events.

Local sea surface temperatures add to extreme precipitation in northeast Australia during La Niña

NASA Astrophysics Data System (ADS)

Evans, Jason P.; Boyer-Souchet, Irène

2012-05-01

This study examines the role played by high sea surface temperatures around northern Australia, in producing the extreme precipitation which occurred during the strong La Niña in December 2010. These extreme rains produced floods that impacted almost 1,300,000 km2, caused billions of dollars in damage, led to the evacuation of thousands of people and resulted in 35 deaths. Through the use of regional climate model simulations the contribution of the observed high sea surface temperatures to the rainfall is quantified. Results indicate that the large-scale atmospheric circulation changes associated with the La Niña event, while associated with above average rainfall in northeast Australia, were insufficient to produce the extreme rainfall and subsequent flooding observed. The presence of high sea surface temperatures around northern Australia added ˜25% of the rainfall total.

Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event.

PubMed

Knebl, M R; Yang, Z-L; Hutchison, K; Maidment, D R

2005-06-01

This paper develops a framework for regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and a hydrological model (HEC-HMS/RAS). The San Antonio River Basin (about 4000 square miles, 10,000 km2) in Central Texas, USA, is the domain of the study because it is a region subject to frequent occurrences of severe flash flooding. A major flood in the summer of 2002 is chosen as a case to examine the modeling framework. The model consists of a rainfall-runoff model (HEC-HMS) that converts precipitation excess to overland flow and channel runoff, as well as a hydraulic model (HEC-RAS) that models unsteady state flow through the river channel network based on the HEC-HMS-derived hydrographs. HEC-HMS is run on a 4 x 4 km grid in the domain, a resolution consistent with the resolution of NEXRAD rainfall taken from the local river authority. Watershed parameters are calibrated manually to produce a good simulation of discharge at 12 subbasins. With the calibrated discharge, HEC-RAS is capable of producing floodplain polygons that are comparable to the satellite imagery. The modeling framework presented in this study incorporates a portion of the recently developed GIS tool named Map to Map that has been created on a local scale and extends it to a regional scale. The results of this research will benefit future modeling efforts by providing a tool for hydrological forecasts of flooding on a regional scale. While designed for the San Antonio River Basin, this regional scale model may be used as a prototype for model applications in other areas of the country.

Assessing the implementation of bias correction in the climate prediction

NASA Astrophysics Data System (ADS)

Nadrah Aqilah Tukimat, Nurul

2018-04-01

An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.

Impact of potential large-scale and medium-scale irrigation on the West African Monsoon and its dependence on location of irrigated area

NASA Astrophysics Data System (ADS)

Eltahir, E. A. B.; IM, E. S.

2014-12-01

This study investigates the impact of potential large-scale (about 400,000 km2) and medium-scale (about 60,000 km2) irrigation on the climate of West Africa using the MIT Regional Climate Model. A new irrigation module is implemented to assess the impact of location and scheduling of irrigation on rainfall distribution over West Africa. A control simulation (without irrigation) and various sensitivity experiments (with irrigation) are performed and compared to discern the effects of irrigation location, size and scheduling. In general, the irrigation-induced surface cooling due to anomalously wet soil tends to suppress moist convection and rainfall, which in turn induces local subsidence and low level anti-cyclonic circulation. These local effects are dominated by a consistent reduction of local rainfall over the irrigated land, irrespective of its location. However, the remote response of rainfall distribution to irrigation exhibits a significant sensitivity to the latitudinal position of irrigation. The low-level northeasterly flow associated with anti-cyclonic circulation centered over the irrigation area can enhance the extent of low level convergence through interaction with the prevailing monsoon flow, leading to significant increase in rainfall. Despite much reduced forcing of irrigation water, the medium-scale irrigation seems to draw the same response as large-scale irrigation, which supports the robustness of the response to irrigation in our modeling system. Both large-scale and medium-scale irrigation experiments show that an optimal irrigation location and scheduling exists that would lead to a more efficient use of irrigation water. The approach of using a regional climate model to investigate the impact of location and size of irrigation schemes may be the first step in incorporating land-atmosphere interactions in the design of location and size of irrigation projects. However, this theoretical approach is still in early stages of development and further research is needed before any practical application in water resources planning. Acknowledgements.This research was supported by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling interdisciplinary research program.

Vertical Profiles of Latent Heat Release and Their Retrieval for TOGA COARE Convective Systems Using a Cloud Resolving Model, SSM/I, and Ship-borne Radar Data

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, S.; Simpson, J.; Olson, W. S.; Johnson, D.; Ferrier, B.; Kummerow, C.; Adler, R.

1999-01-01

Latent heating profiles associated with three (TOGA COARE) Tropical Ocean and Global Atmosphere Coupled Ocean Atmosphere Response Experiment active convective episodes (December 10-17 1992; December 19-27 1992; and February 9-13 1993) are examined using the Goddard Cumulus Ensemble (GCE) Model and retrieved by using the Goddard Convective and Stratiform Heating (CSH) algorithm . The following sources of rainfall information are input into the CSH algorithm: Special Sensor Microwave Imager (SSM/1), Radar and the GCE model. Diagnostically determined latent heating profiles calculated using 6 hourly soundings are used for validation. The GCE model simulated rainfall and latent heating profiles are in excellent agreement with those estimated by soundings. In addition, the typical convective and stratiform heating structures (or shapes) are well captured by the GCE model. Radar measured rainfall is smaller than that both estimated by the GCE model and SSM/I in all three different COARE IFA periods. SSM/I derived rainfall is more than the GCE model simulated for the December 19-27 and February 9-13 periods, but is in excellent agreement with the GCE model for the December 10-17 period. The GCE model estimated stratiform amount is about 50% for December 19-27, 42% for December 11-17 and 56% for the February 9-13 case. These results are consistent with large-scale analyses. The accurate estimates of stratiform amount is needed for good latent heating retrieval. A higher (lower) percentage of stratiform rain can imply a maximum heating rate at a higher (lower) altitude. The GCE model always simulates more stratiform rain (10 to 20%) than the radar for all three convective episodes. SSM/I derived stratiform amount is about 37% for December 19-27, 48% for December 11-17 and 41% for the February 9-13 case. Temporal variability of CSH algorithm retrieved latent heating profiles using either GCE model simulated or radar estimated rainfall and stratiform amount is in good agreement with that diagnostically determined for all three periods. However, less rainfall and a smaller stratiform percentage estimated by radar resulted in a weaker (underestimated) latent heating profile and a lower maximum latent heating level compared to those determined diagnostically. Rainfall information from SSM/I can not retrieve individual convective events due to poor temporal sampling. Nevertheless, this study suggests that a good 4r, rainfall retrieval from SSM/I for a convective event always leads to a good latent heating retrieval. Sensitivity testing has been performed and the results indicate that the SSM/I derived time averaged stratiform amount may be underestimated for December 19-27. Time averaged heating profiles derived from SSM/I, however, are not in bad agreement with those derived by soundings for the December 10-17 convective period. The heating retrievals may be more accurate for longer time scales provided there is no bias in the sampling.

Modelling urban rainfall-runoff responses using an experimental, two-tiered physical modelling environment

NASA Astrophysics Data System (ADS)

Green, Daniel; Pattison, Ian; Yu, Dapeng

2016-04-01

Surface water (pluvial) flooding occurs when rainwater from intense precipitation events is unable to infiltrate into the subsurface or drain via natural or artificial drainage channels. Surface water flooding poses a serious hazard to urban areas across the world, with the UK's perceived risk appearing to have increased in recent years due to surface water flood events seeming more severe and frequent. Surface water flood risk currently accounts for 1/3 of all UK flood risk, with approximately two million people living in urban areas at risk of a 1 in 200-year flood event. Research often focuses upon using numerical modelling techniques to understand the extent, depth and severity of actual or hypothetical flood scenarios. Although much research has been conducted using numerical modelling, field data available for model calibration and validation is limited due to the complexities associated with data collection in surface water flood conditions. Ultimately, the data which numerical models are based upon is often erroneous and inconclusive. Physical models offer a novel, alternative and innovative environment to collect data within, creating a controlled, closed system where independent variables can be altered independently to investigate cause and effect relationships. A physical modelling environment provides a suitable platform to investigate rainfall-runoff processes occurring within an urban catchment. Despite this, physical modelling approaches are seldom used in surface water flooding research. Scaled laboratory experiments using a 9m2, two-tiered 1:100 physical model consisting of: (i) a low-cost rainfall simulator component able to simulate consistent, uniformly distributed (>75% CUC) rainfall events of varying intensity, and; (ii) a fully interchangeable, modular plot surface have been conducted to investigate and quantify the influence of a number of terrestrial and meteorological factors on overland flow and rainfall-runoff patterns within a modelled urban setting. Terrestrial factors investigated include altering the physical model's catchment slope (0°- 20°), as well as simulating a number of spatially-varied impermeability and building density/configuration scenarios. Additionally, the influence of different storm dynamics and intensities were investigated. Preliminary results demonstrate that rainfall-runoff responses in the physical modelling environment are highly sensitive to slight increases in catchment gradient and rainfall intensity and that more densely distributed building layouts significantly increase peak flows recorded at the physical model outflow when compared to sparsely distributed building layouts under comparable simulated rainfall conditions.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Rainfall simulation experiments in the Southwestern USA using the Walnut Gulch rainfall simulator

USDA-ARS?s Scientific Manuscript database

The dataset contains hydrological, erosion, vegetation, ground cover, and other supplementary information from 272 rainfall simulation experiments conducted on 23 semi-arid rangeland locations in Arizona and Nevada between 2002 and 2013. On 30% of the plots simulations were conducted up to five time...

Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length

NASA Astrophysics Data System (ADS)

Guan, Kaiyu; Good, Stephen P.; Caylor, Kelly K.; Medvigy, David; Pan, Ming; Wood, Eric F.; Sato, Hisashi; Biasutti, Michela; Chen, Min; Ahlström, Anders; Xu, Xiangtao

2018-02-01

There is growing evidence of ongoing changes in the statistics of intra-seasonal rainfall variability over large parts of the world. Changes in annual total rainfall may arise from shifts, either singly or in a combination, of distinctive intra-seasonal characteristics -i.e. rainfall frequency, rainfall intensity, and rainfall seasonality. Understanding how various ecosystems respond to the changes in intra-seasonal rainfall characteristics is critical for predictions of future biome shifts and ecosystem services under climate change, especially for arid and semi-arid ecosystems. Here, we use an advanced dynamic vegetation model (SEIB-DGVM) coupled with a stochastic rainfall/weather simulator to answer the following question: how does the productivity of ecosystems respond to a given percentage change in the total seasonal rainfall that is realized by varying only one of the three rainfall characteristics (rainfall frequency, intensity, and rainy season length)? We conducted ensemble simulations for continental Africa for a realistic range of changes (-20% ~ +20%) in total rainfall amount. We find that the simulated ecosystem productivity (measured by gross primary production, GPP) shows distinctive responses to the intra-seasonal rainfall characteristics. Specifically, increase in rainfall frequency can lead to 28% more GPP increase than the same percentage increase in rainfall intensity; in tropical woodlands, GPP sensitivity to changes in rainy season length is ~4 times larger than to the same percentage changes in rainfall frequency or intensity. In contrast, shifts in the simulated biome distribution are much less sensitive to intra-seasonal rainfall characteristics than they are to total rainfall amount. Our results reveal three major distinctive productivity responses to seasonal rainfall variability—‘chronic water stress’, ‘acute water stress’ and ‘minimum water stress’ - which are respectively associated with three broad spatial patterns of African ecosystem physiognomy, i.e. savannas, woodlands, and tropical forests.

Rainfall Stochastic models

NASA Astrophysics Data System (ADS)

Campo, M. A.; Lopez, J. J.; Rebole, J. P.

2012-04-01

This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series were recorded every ten minutes and hourly, aggregated. Preliminary results show adequate simulation of the main features of rain. Main variables are well simulated for time series of ten minutes, also over one hour precipitation time series, which are those that generate higher rainfall hydrologic design. For coarse scales, less than one hour, rainfall durations are not appropriate under the simulation. A hypothesis may be an excessive number of simulated events, which causes further fragmentation of storms, resulting in an excess of rain "short" (less than 1 hour), and therefore also among rain events, compared with the ones that occur in the actual series.

A space-time multifractal analysis on radar rainfall sequences from central Poland

NASA Astrophysics Data System (ADS)

Licznar, Paweł; Deidda, Roberto

2014-05-01

Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal analysis is carried out assuming Taylor's hypothesis to hold and the advection velocity needed to rescale the time dimension is assumed to be equal about 16 km/h. This assumption is verified by the analysis of autocorrelation functions along the x and y directions of "rainfall cubes" and along the time axis rescaled with assumed advection velocity. In general for analyzed rainfall sequences scaling is observed for spatial scales ranging from 4 to 256 km and for timescales from 15 min to 16 hours. However in most cases scaling break is identified for spatial scales between 4 and 8, corresponding to spatial dimensions of 16 km to 32 km. It is assumed that the scaling break occurrence at these particular scales in central Poland conditions could be at least partly explained by the rainfall mesoscale gap (on the edge of meso-gamma, storm-scale and meso-beta scale).

Assessing manure management strategies through small-plot research and whole-farm modeling

USGS Publications Warehouse

Garcia, A.M.; Veith, T.L.; Kleinman, P.J.A.; Rotz, C.A.; Saporito, L.S.

2008-01-01

Plot-scale experimentation can provide valuable insight into the effects of manure management practices on phosphorus (P) runoff, but whole-farm evaluation is needed for complete assessment of potential trade offs. Artificially-applied rainfall experimentation on small field plots and event-based and long-term simulation modeling were used to compare P loss in runoff related to two dairy manure application methods (surface application with and without incorporation by tillage) on contrasting Pennsylvania soils previously under no-till management. Results of single-event rainfall experiments indicated that average dissolved reactive P losses in runoff from manured plots decreased by up to 90% with manure incorporation while total P losses did not change significantly. Longer-term whole farm simulation modeling indicated that average dissolved reactive P losses would decrease by 8% with manure incorporation while total P losses would increase by 77% due to greater erosion from fields previously under no-till. Differences in the two methods of inference point to the need for caution in extrapolating research findings. Single-event rainfall experiments conducted shortly after manure application simulate incidental transfers of dissolved P in manure to runoff, resulting in greater losses of dissolved reactive P. However, the transfer of dissolved P in applied manure diminishes with time. Over the annual time frame simulated by whole farm modeling, erosion processes become more important to runoff P losses. Results of this study highlight the need to consider the potential for increased erosion and total P losses caused by soil disturbance during incorporation. This study emphasizes the ability of modeling to estimate management practice effectiveness at the larger scales when experimental data is not available.

Simulation of the Summer Monsoon Rainfall over East Asia using the NCEP GFS Cumulus Parameterization at Different Horizontal Resolutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, Kyo-Sun; Hong, Song You; Yoon, Jin-Ho

2014-10-01

The most recent version of Simplified Arakawa-Schubert (SAS) cumulus scheme in National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) (GFS SAS) has been implemented into the Weather and Research Forecasting (WRF) model with a modification of triggering condition and convective mass flux to become depending on model’s horizontal grid spacing. East Asian Summer Monsoon of 2006 from June to August is selected to evaluate the performance of the modified GFS SAS scheme. Simulated monsoon rainfall with the modified GFS SAS scheme shows better agreement with observation compared to the original GFS SAS scheme. The original GFS SAS schememore » simulates the similar ratio of subgrid-scale precipitation, which is calculated from a cumulus scheme, against total precipitation regardless of model’s horizontal grid spacing. This is counter-intuitive because the portion of resolved clouds in a grid box should be increased as the model grid spacing decreases. This counter-intuitive behavior of the original GFS SAS scheme is alleviated by the modified GFS SAS scheme. Further, three different cumulus schemes (Grell and Freitas, Kain and Fritsch, and Betts-Miller-Janjic) are chosen to investigate the role of a horizontal resolution on simulated monsoon rainfall. The performance of high-resolution modeling is not always enhanced as the spatial resolution becomes higher. Even though improvement of probability density function of rain rate and long wave fluxes by the higher-resolution simulation is robust regardless of a choice of cumulus parameterization scheme, the overall skill score of surface rainfall is not monotonically increasing with spatial resolution.« less

On the climate model simulation of Indian monsoon low pressure systems and the effect of remote disturbances and systematic biases

NASA Astrophysics Data System (ADS)

Levine, Richard C.; Martin, Gill M.

2018-06-01

Monsoon low pressure systems (LPS) are synoptic-scale systems forming over the Indian monsoon trough region, contributing substantially to seasonal mean summer monsoon rainfall there. Many current global climate models (GCMs), including the Met Office Unified Model (MetUM), show deficient rainfall in this region, much of which has previously been attributed to remote systematic biases such as excessive equatorial Indian Ocean (EIO) convection, while also substantially under-representing LPS and associated rainfall as they travel westwards across India. Here the sources and sensitivities of LPS to local, remote and short-timescale forcing are examined, in order to understand the poor representation in GCMs. An LPS tracking method is presented using TRACK feature tracking software for comparison between re-analysis data-sets, MetUM GCM and regional climate model (RCM) simulations. RCM simulations, at similar horizontal resolution to the GCM and forced with re-analysis data at the lateral boundaries, are carried out with different domains to examine the effects of remote biases. The results suggest that remote biases contribute significantly to the poor simulation of LPS in the GCM. As these remote systematic biases are common amongst many current GCMs, it is likely that GCMs are intrinsically capable of representing LPS, even at relatively low resolution. The main problem areas are time-mean excessive EIO convection and poor representation of precursor disturbances transmitted from the Western Pacific. The important contribution of the latter is established using RCM simulations forced by climatological 6-hourly lateral boundary conditions, which also highlight the role of LPS in moving rainfall from steep orography towards Central India.

Along the Rainfall-Runoff Chain: From Scaling of Greatest Point Rainfall to Global Change Attribution

NASA Astrophysics Data System (ADS)

Fraedrich, K.

2014-12-01

Processes along the continental rainfall-runoff chain cover a wide range of time and space scales which are presented here combining observations (ranging from minutes to decades) and minimalist concepts. (i) Rainfall, which can be simulated by a censored first-order autoregressive process (vertical moisture fluxes), exhibits 1/f-spectra if presented as binary events (tropics), while extrema world wide increase with duration according to Jennings' scaling law. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function not unlike physical systems at criticality and the short and long return times of extremes are Weibull-distributed. Atmospheric and soil moisture variabilities are also discussed. (iii) Soil moisture (in a bucket), whose variability is interpreted by a biased coinflip Ansatz for rainfall events, adds an equation of state to energy and water flux balances comprising Budyko's frame work for quasi-stationary watershed analysis. Eco-hydrologic state space presentations in terms of surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation) allow attributions of state change to external (or climate) and internal (or anthropogenic) causes. Including the vegetation-greenness index (NDVI) as an active tracer extends the eco-hydrologic state space analysis to supplement the common geographical presentations. Two examples demonstrate the approach combining ERA and MODIS data sets: (a) global geobotanic classification by combining first and second moments of the dryness ratio (net radiation over precipitation) and (b) regional attributions (Tibetan Plateau) of vegetation changes.

Critical scales to explain urban hydrological response: an application in Cranbrook, London

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-Claire; Gaitan, Santiago; Ochoa Rodriguez, Susana; van de Giesen, Nick

2018-04-01

Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response.

The International year of soils: thoughts on future directions for experiments in soil erosion research

NASA Astrophysics Data System (ADS)

Kuhn, Nikolaus J.

2015-04-01

The 2015 UN Year of Soils (IYS), implemented by the FAO, aims to increase awareness and understanding of the importance of soil for food security and essential ecosystem functions. The IYS has six specific objectives, ranging from raising the awareness among civil society and decision makers about the profound importance of soils, to the development of policies supporting the sustainable use of the non-renewable soil resource. For scientists and academic teachers using experiments to study soil erosion processes, two objectives appear of particular relevance. First is need for the rapid capacity enhancement for soil information collection and monitoring at all levels (global, regional and national). While at first glance, this objective appears to relate mostly to traditional mapping, sampling and monitoring, the threat of large-scale soil loss, at least with regards to their ecosystem services, illustrates the need for approaches of studying soils that avoids such irreversible destruction. Relying on often limited data and their extrapolation does not cover this need for soil information because rapid change of the drivers of change itself carry the risk of unprecedented soil reactions not covered by existing data sets. Experiments, on the other hand, offer the possibility to simulate and analyze future soil change in great detail. Furthermore, carefully designed experiments may also limit the actual effort involved in collecting the specific required information, e.g. by applying tests designed to study soil system behavior under controlled conditions, compared to field monitoring. For rainfall simulation, experiments should therefore involve the detailed study of erosion processes and include detailed recording and reporting of soil and rainfall properties. The development of a set of standardised rainfall simulations would widen the use data collected by such experiments. A second major area for rainfall simulation lies in the the education of the public about the crucial role soil plays in food security, climate change adaptation and mitigation, essential ecosystem services, poverty alleviation and sustainable development. While erosion monitoring and modeling, as well as erosion risk assessment maps provide a solid foundation for decision makers, the attention of the public for "dirt" is often much easier to achieve by setting up a rainfall simulation experiment that illustrates the connection between a process, such as rainfall and runoff observed in daily life, and its causes and consequences. Exploring the potential of rainfall simulation experiments as an outreach tool should therefore be part of the soil science, geomorphology and hydrology community during the IYS 2015 and beyond.

How runoff begins (and ends): characterizing hydrologic response at the catchment scale

USGS Publications Warehouse

Mirus, Benjamin B.; Loague, Keith

2013-01-01

Improved understanding of the complex dynamics associated with spatially and temporally variable runoff response is needed to better understand the hydrology component of interdisciplinary problems. The objective of this study was to quantitatively characterize the environmental controls on runoff generation for the range of different streamflow-generation mechanisms illustrated in the classic Dunne diagram. The comprehensive physics-based model of coupled surface-subsurface flow, InHM, is employed in a heuristic mode. InHM has been employed previously to successfully simulate the observed hydrologic response at four diverse, well-characterized catchments, which provides the foundation for this study. The C3 and CB catchments are located within steep, forested terrain; the TW and R5 catchments are located in gently sloping rangeland. The InHM boundary-value problems for these four catchments provide the corner-stones for alternative simulation scenarios designed to address the question of how runoff begins (and ends). Simulated rainfall-runoff events are used to systematically explore the impact of soil-hydraulic properties and rainfall characteristics. This approach facilitates quantitative analysis of both integrated and distributed hydrologic responses at high-spatial and temporal resolution over the wide range of environmental conditions represented by the four catchments. The results from 140 unique simulation scenarios illustrate how rainfall intensity/depth, subsurface permeability contrasts, characteristic curve shapes, and topography provide important controls on the hydrologic-response dynamics. The processes by which runoff begins (and ends) are shown, in large part, to be defined by the relative rates of rainfall, infiltration, lateral flow convergence, and storage dynamics within the variably saturated soil layers.

Conceptual modelling of E. coli in urban stormwater drains, creeks and rivers

NASA Astrophysics Data System (ADS)

Jovanovic, Dusan; Hathaway, Jon; Coleman, Rhys; Deletic, Ana; McCarthy, David T.

2017-12-01

Accurate estimation of faecal microorganism levels in water systems, such as stormwater drains, creeks and rivers, is needed for appropriate assessment of impacts on receiving water bodies and the risks to human health. The underlying hypothesis for this work is that a single conceptual model (the MicroOrganism Prediction in Urban Stormwater model - i.e. MOPUS) can adequately simulate microbial dynamics over a variety of water systems and wide range of scales; something which has not been previously tested. Additionally, the application of radar precipitation data for improvement of the model performance at these scales via more accurate areal averaged rainfall intensities was tested. Six comprehensive Escherichia coli (E. coli) datasets collected from five catchments in south-eastern Australia and one catchment in Raleigh, USA, were used to calibrate the model. The MOPUS rainfall-runoff model performed well at all scales (Nash-Sutcliffe E for instantaneous flow rates between 0.70 and 0.93). Sensitivity analysis showed that wet weather urban stormwater flows can be modelled with only three of the five rainfall runoff model parameters: routing coefficient (K), effective imperviousness (IMP) and time of concentration (TOC). The model's performance for representing instantaneous E. coli fluctuations ranged from 0.17 to 0.45 in catchments drained via pipe or open creek, and was the highest for a large riverine catchment (0.64); performing similarly, if not better, than other microbial models in literature. The model could also capture the variability in event mean concentrations (E = 0.17-0.57) and event loads (E = 0.32-0.97) at all scales. Application of weather radar-derived rainfall inputs caused lower overall performance compared to using gauged rainfall inputs in representing both flow and E. coli levels in urban drain catchments, with the performance improving with increasing catchment size and being comparable to the models that use gauged rainfall inputs at the large riverine catchment. These results demonstrate the potential of the MOPUS model and its ability to be applied to a wide range of catchment scales, including large riverine systems.

A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations.

PubMed

Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne

2016-01-01

Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture.

A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations

PubMed Central

Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne

2016-01-01

Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture. PMID:27003834

Integrated hydrologic modeling: Effects of spatial scale, discretization and initialization

NASA Astrophysics Data System (ADS)

Seck, A.; Welty, C.; Maxwell, R. M.

2011-12-01

Groundwater discharge contributes significantly to the annual flows of Chesapeake Bay tributaries and is presumed to contribute to the observed lag time between the implementation of management actions and the environmental response in the Chesapeake Bay. To investigate groundwater fluxes and flow paths and interaction with surface flow, we have developed a fully distributed integrated hydrologic model of the Chesapeake Bay Watershed using ParFlow. Here we present a comparison of model spatial resolution and initialization methods. We have studied the effect of horizontal discretization on overland flow processes at a range of scales. Three nested model domains have been considered: the Monocacy watershed (5600 sq. km), the Potomac watershed (92000 sq. km) and the Chesapeake Bay watershed (400,000 sq. km). Models with homogeneous subsurface and topographically-derived slopes were evaluated at 500-m, 1000-m, 2000-m, and 4000-m grid resolutions. Land surface slopes were derived from resampled DEMs and corrected using stream networks. Simulation results show that the overland flow processes are reasonably well represented with a resolution up to 2000 m. We observe that the effects of horizontal resolution dissipate with larger scale models. Using a homogeneous model that includes subsurface and surface terrain characteristics, we have evaluated various initialization methods for the integrated Monocacy watershed model. This model used several options for water table depths and two rainfall forcing methods including (1) a synthetic rainfall-recession cycle corresponding to the region's average annual rainfall rate, and (2) an initial shut-off of rainfall forcing followed by a rainfall-recession cycling. Results show the dominance of groundwater generated runoff during a first phase of the simulation followed by a convergence towards more balanced runoff generation mechanisms. We observe that the influence of groundwater runoff increases in dissected relief areas characterized by high slope magnitudes. This is due to the increase in initial water table gradients in these regions. As a result, in the domain conditions for this study, an initial shut-off of rainfall forcing proved to be the more efficient initialization method. The initialized model is then coupled with a Land Surface Model (CLM). Ongoing work includes coupling a heterogeneous subsurface field with spatially variable meteorological forcing using the National Land Data Assimilation System (NLDAS) data products. Seasonal trends of groundwater levels for current and pre-development conditions of the basin will be compared.

A new time-space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale

Treesearch

Takahiro Sayama; Jeffrey J. McDonnell

2009-01-01

Hydrograph source components and stream water residence time are fundamental behavioral descriptors of watersheds but, as yet, are poorly represented in most rainfall-runoff models. We present a new time-space accounting scheme (T-SAS) to simulate the pre-event and event water fractions, mean residence time, and spatial source of streamflow at the watershed scale. We...

The stochastic runoff-runon process: Extending its analysis to a finite hillslope

NASA Astrophysics Data System (ADS)

Jones, O. D.; Lane, P. N. J.; Sheridan, G. J.

2016-10-01

The stochastic runoff-runon process models the volume of infiltration excess runoff from a hillslope via the overland flow path. Spatial variability is represented in the model by the spatial distribution of rainfall and infiltration, and their ;correlation scale;, that is, the scale at which the spatial correlation of rainfall and infiltration become negligible. Notably, the process can produce runoff even when the mean rainfall rate is less than the mean infiltration rate, and it displays a gradual increase in net runoff as the rainfall rate increases. In this paper we present a number of contributions to the analysis of the stochastic runoff-runon process. Firstly we illustrate the suitability of the process by fitting it to experimental data. Next we extend previous asymptotic analyses to include the cases where the mean rainfall rate equals or exceeds the mean infiltration rate, and then use Monte Carlo simulation to explore the range of parameters for which the asymptotic limit gives a good approximation on finite hillslopes. Finally we use this to obtain an equation for the mean net runoff, consistent with our asymptotic results but providing an excellent approximation for finite hillslopes. Our function uses a single parameter to capture spatial variability, and varying this parameter gives us a family of curves which interpolate between known upper and lower bounds for the mean net runoff.

Water Isotope Proxy-Proxy and Proxy-Model Convergence for Late Pleistocene East Asian Monsoon Rainfall Reconstructions

NASA Astrophysics Data System (ADS)

Clemens, S. C.; Holbourn, A.; Kubota, Y.; Lee, K. E.; Liu, Z.; Chen, G.

2017-12-01

Confidence in reconstruction of East Asian paleomonsoon rainfall using precipitation isotope proxies is a matter of considerable debate, largely due to the lack of correlation between precipitation amount and isotopic composition in the present climate. We present four new, very highly resolved records spanning the past 300,000 years ( 200 year sample spacing) from IODP Site U1429 in the East China Sea. We demonstrate that all the orbital- and millennial-scale variance in the onshore Yangtze River Valley speleothem δ18O record1 is also embedded in the offshore Site U1429 seawater δ18O record (derived from the planktonic foraminifer Globigerinoides ruber and sea surface temperature reconstructions). Signal replication in these two independent terrestrial and marine archives, both controlled by the same monsoon system, uniquely identifies δ18O of precipitation as the primary driver of the precession-band variance in both records. This proxy-proxy convergence also eliminates a wide array of other drivers that have been called upon as potential contaminants to the precipitation δ18O signal recorded by these proxies. We compare East Asian precipitation isotope proxy records to precipitation amount from a CCSM3 transient climate model simulation of the past 300,000 years using realistic insolation, ice volume, greenhouse gasses, and sea level boundary conditions. This model-proxy comparison suggests that both Yangtze River Valley precipitation isotope proxies (seawater and speleothem δ18O) track changes in summer-monsoon rainfall amount at orbital time scales, as do precipitation isotope records from the Pearl River Valley2 (leaf wax δ2H) and Borneo3 (speleothem δ18O). Notably, these proxy records all have significantly different spectral structure indicating strongly regional rainfall patterns that are also consistent with model results. Transient, isotope-enabled model simulations will be necessary to more thoroughly evaluate these promising results, and to evaluate potentially distinct regional mechanisms linking rainfall amount to precipitation isotopes at orbital and millennial time scales in other monsoon regions. 1 Cheng et al., 10.1038/nature18591 2 Thomas et al., 10.1130/G36289.1 3 Carolin et al., 10.1016/j.epsl.2016.01.028

Characterization of rainfall-runoff response and estimation of the effect of wetland restoration on runoff, Heron Lake Basin, southwestern Minnesota, 1991-97

USGS Publications Warehouse

Jones, Perry M.; Winterstein, Thomas A.

2000-01-01

The U.S. Geological Survey (USGS), in cooperation with the Minnesota Department of Natural Resources and the Heron Lake Watershed District, conducted a study to characterize the rainfall-runoff response and to examine the effects of wetland restoration on the rainfall-runoff response within the Heron Lake Basin in southwestern Minnesota. About 93 percent of the land cover in the Heron Lake Basin consists of agricultural lands, consisting almost entirely of row crops, with less than one percent consisting of wetlands. The Hydrological Simulation Program – Fortran (HSPF), Version 10, was calibrated to continuous discharge data and used to characterize rainfall-runoff responses in the Heron Lake Basin between May 1991 and August 1997. Simulation of the Heron Lake Basin was done as a two-step process: (1) simulations of five small subbasins using data from August 1995 through August 1997, and (2) simulations of the two large basins, Jack and Okabena Creek Basins, using data from May 1991 through September 1996. Simulations of the five small subbasins was done to determine basin parameters for the land segments and assess rainfall-runoff response variability in the basin. Simulations of the two larger basins were done to verify the basin parameters and assess rainfall-runoff responses over a larger area and for a longer time period. Best-fit calibrations of the five subbasin simulations indicate that the rainfall-runoff response is uniform throughout the Heron Lake Basin, and 48 percent of the total rainfall for storms becomes direct (surface and interflow) runoff. Rainfall-runoff response variations result from variations in the distribution, intensity, timing, and duration of rainfall; soil moisture; evapotranspiration rates; and the presence of lakes in the basin. In the spring, the amount and distribution of rainfall tends to govern the runoff response. High evapotranspiration rates in the summer result in a depletion of moisture from the soils, substantially affecting the rainfall-runoff relation. Five wetland restoration simulations were run for each of five subbasins using data from August 1995 through August 1997, and for the two larger basins, Jack and Okabena Creek Basins, using data from May 1991 through September 1996. Results from linear regression analysis of total simulated direct runoff and total rainfall data for simulated storms in the wetland-restoration simulations indicate that the portion of total rainfall that becomes runoff will be reduced by 46 percent if 45 percent of current cropland is converted to wetland. The addition of wetlands reduced peak runoff in most of the simulations, but the reduction varied with antecedent soil moisture, the magnitude of the peak flow, and the presence of current wetlands and lakes. Reductions in the simulated total and peak runoff from the Jack Creek Basin for most of the simulated storms were greatest when additional wetlands were simulated in the North Branch Jack Creek or the Upper Jack Creek Subbasins. In the Okabena Creek Basin, reductions in simulated peak runoff for most of the storms were greatest when additional wetlands were simulated in the Lower Okabena Creek Subbasin.

Performance of ICTP's RegCM4 in Simulating the Rainfall Characteristics over the CORDEX-SEA Domain

NASA Astrophysics Data System (ADS)

Neng Liew, Ju; Tangang, Fredolin; Tieh Ngai, Sheau; Chung, Jing Xiang; Narisma, Gemma; Cruz, Faye Abigail; Phan Tan, Van; Thanh, Ngo-Duc; Santisirisomboon, Jerasron; Milindalekha, Jaruthat; Singhruck, Patama; Gunawan, Dodo; Satyaningsih, Ratna; Aldrian, Edvin

2015-04-01

The performance of the RegCM4 in simulating rainfall variations over the Southeast Asia regions was examined. Different combinations of six deep convective parameterization schemes, namely i) Grell scheme with Arakawa-Schubert closure assumption, ii) Grell scheme with Fritch-Chappel closure assumption, iii) Emanuel MIT scheme, iv) mixed scheme with Emanuel MIT scheme over the Ocean and the Grell scheme over the land, v) mixed scheme with Grell scheme over the land and Emanuel MIT scheme over the ocean and (vi) Kuo scheme, and three ocean flux treatments were tested. In order to account for uncertainties among the observation products, four different gridded rainfall products were used for comparison. The simulated climate is generally drier over the equatorial regions and slightly wetter over the mainland Indo-China compare to the observation. However, simulation with MIT cumulus scheme used over the land area consistently produces large amplitude of positive rainfall biases, although it simulates more realistic annual rainfall variations. The simulations are found less sensitive to treatment of ocean fluxes. Although the simulations produced the rainfall climatology well, all of them simulated much stronger interannual variability compare to that of the observed. Nevertheless, the time evolution of the inter-annual variations was well reproduced particularly over the eastern part of maritime continent. Over the mainland Southeast Asia (SEA), unrealistic rainfall anomalies processes were simulated. The lacking of summer season air-sea interaction results in strong oceanic forcings over the regions, leading to positive rainfall anomalies during years with warm ocean temperature anomalies. This incurs much stronger atmospheric forcings on the land surface processes compare to that of the observed. A score ranking system was designed to rank the simulations according to their performance in reproducing different aspects of rainfall characteristics. The result suggests that the simulation with Emanuel MIT convective scheme and BATs land surface scheme produces better collective performance compare to the rest of the simulations.

Quasi-continuous stochastic simulation framework for flood modelling

NASA Astrophysics Data System (ADS)

Moustakis, Yiannis; Kossieris, Panagiotis; Tsoukalas, Ioannis; Efstratiadis, Andreas

2017-04-01

Typically, flood modelling in the context of everyday engineering practices is addressed through event-based deterministic tools, e.g., the well-known SCS-CN method. A major shortcoming of such approaches is the ignorance of uncertainty, which is associated with the variability of soil moisture conditions and the variability of rainfall during the storm event.In event-based modeling, the sole expression of uncertainty is the return period of the design storm, which is assumed to represent the acceptable risk of all output quantities (flood volume, peak discharge, etc.). On the other hand, the varying antecedent soil moisture conditions across the basin are represented by means of scenarios (e.g., the three AMC types by SCS),while the temporal distribution of rainfall is represented through standard deterministic patterns (e.g., the alternative blocks method). In order to address these major inconsistencies,simultaneously preserving the simplicity and parsimony of the SCS-CN method, we have developed a quasi-continuous stochastic simulation approach, comprising the following steps: (1) generation of synthetic daily rainfall time series; (2) update of potential maximum soil moisture retention, on the basis of accumulated five-day rainfall; (3) estimation of daily runoff through the SCS-CN formula, using as inputs the daily rainfall and the updated value of soil moisture retention;(4) selection of extreme events and application of the standard SCS-CN procedure for each specific event, on the basis of synthetic rainfall.This scheme requires the use of two stochastic modelling components, namely the CastaliaR model, for the generation of synthetic daily data, and the HyetosMinute model, for the disaggregation of daily rainfall to finer temporal scales. Outcomes of this approach are a large number of synthetic flood events, allowing for expressing the design variables in statistical terms and thus properly evaluating the flood risk.

A Bivariate Mixed Distribution with a Heavy-tailed Component and its Application to Single-site Daily Rainfall Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Chao ..; Singh, Vijay P.; Mishra, Ashok K.

2013-02-06

This paper presents an improved brivariate mixed distribution, which is capable of modeling the dependence of daily rainfall from two distinct sources (e.g., rainfall from two stations, two consecutive days, or two instruments such as satellite and rain gauge). The distribution couples an existing framework for building a bivariate mixed distribution, the theory of copulae and a hybrid marginal distribution. Contributions of the improved distribution are twofold. One is the appropriate selection of the bivariate dependence structure from a wider admissible choice (10 candidate copula families). The other is the introduction of a marginal distribution capable of better representing lowmore » to moderate values as well as extremes of daily rainfall. Among several applications of the improved distribution, particularly presented here is its utility for single-site daily rainfall simulation. Rather than simulating rainfall occurrences and amounts separately, the developed generator unifies the two processes by generalizing daily rainfall as a Markov process with autocorrelation described by the improved bivariate mixed distribution. The generator is first tested on a sample station in Texas. Results reveal that the simulated and observed sequences are in good agreement with respect to essential characteristics. Then, extensive simulation experiments are carried out to compare the developed generator with three other alternative models: the conventional two-state Markov chain generator, the transition probability matrix model and the semi-parametric Markov chain model with kernel density estimation for rainfall amounts. Analyses establish that overall the developed generator is capable of reproducing characteristics of historical extreme rainfall events and is apt at extrapolating rare values beyond the upper range of available observed data. Moreover, it automatically captures the persistence of rainfall amounts on consecutive wet days in a relatively natural and easy way. Another interesting observation is that the recognized ‘overdispersion’ problem in daily rainfall simulation ascribes more to the loss of rainfall extremes than the under-representation of first-order persistence. The developed generator appears to be a sound option for daily rainfall simulation, especially in particular hydrologic planning situations when rare rainfall events are of great importance.« less

On the use of satellite-based estimates of rainfall temporal distribution to simulate the potential for malaria transmission in rural Africa

NASA Astrophysics Data System (ADS)

Yamana, Teresa K.; Eltahir, Elfatih A. B.

2011-02-01

This paper describes the use of satellite-based estimates of rainfall to force the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a hydrology-based mechanistic model of malaria transmission. We first examined the temporal resolution of rainfall input required by HYDREMATS. Simulations conducted over Banizoumbou village in Niger showed that for reasonably accurate simulation of mosquito populations, the model requires rainfall data with at least 1 h resolution. We then investigated whether HYDREMATS could be effectively forced by satellite-based estimates of rainfall instead of ground-based observations. The Climate Prediction Center morphing technique (CMORPH) precipitation estimates distributed by the National Oceanic and Atmospheric Administration are available at a 30 min temporal resolution and 8 km spatial resolution. We compared mosquito populations simulated by HYDREMATS when the model is forced by adjusted CMORPH estimates and by ground observations. The results demonstrate that adjusted rainfall estimates from satellites can be used with a mechanistic model to accurately simulate the dynamics of mosquito populations.

TRMM- and GPM-based precipitation analysis and modelling in the Tropical Andes

NASA Astrophysics Data System (ADS)

Manz, Bastian; Buytaert, Wouter; Zulkafli, Zed; Onof, Christian

2016-04-01

Despite wide-spread applications of satellite-based precipitation products (SPPs) throughout the TRMM-era, the scarcity of ground-based in-situ data (high density gauge networks, rainfall radar) in many hydro-meteorologically important regions, such as tropical mountain environments, has limited our ability to evaluate both SPPs and individual satellite-based sensors as well as accurately model or merge rainfall at high spatial resolutions, particularly with respect to extremes. This has restricted both the understanding of sensor behaviour and performance controls in such regions as well as the accuracy of precipitation estimates and respective hydrological applications ranging from water resources management to early warning systems. Here we report on our recent research into precipitation analysis and modelling using various TRMM and GPM products (2A25, 3B42 and IMERG) in the tropical Andes. In an initial study, 78 high-frequency (10-min) recording gauges in Colombia and Ecuador are used to generate a ground-based validation dataset for evaluation of instantaneous TRMM Precipitation Radar (TPR) overpasses from the 2A25 product. Detection ability, precipitation time-series, empirical distributions and statistical moments are evaluated with respect to regional climatological differences, seasonal behaviour, rainfall types and detection thresholds. Results confirmed previous findings from extra-tropical regions of over-estimation of low rainfall intensities and under-estimation of the highest 10% of rainfall intensities by the TPR. However, in spite of evident regionalised performance differences as a function of local climatological regimes, the TPR provides an accurate estimate of climatological annual and seasonal rainfall means. On this basis, high-resolution (5 km) climatological maps are derived for the entire tropical Andes. The second objective of this work is to improve the local precipitation estimation accuracy and representation of spatial patterns of extreme rainfall probabilities over the region. For this purpose, an ensemble of high-resolution rainfall fields is generated by stochastic simulation using space-time averaged, coarse-scale (daily, 0.25°) satellite-based rainfall inputs (TRMM 3B42/ -RT) and the high-resolution climatological information derived from the TPR as spatial disaggregation proxies. For evaluation and merging, gridded ground-based rainfall fields are generated from gauge data using sequential simulation. Satellite and ground-based ensembles are subsequently merged using an inverse error weighting scheme. The model was tested over a case study in the Colombian Andes with optional coarse-scale bias correction prior to disaggregation and merging. The resulting outputs were assessed in the context of Generalized Extreme Value theory and showed improved estimation of extreme rainfall probabilities compared to the original TMPA inputs. Initial findings using GPM-IMERG inputs are also presented.

Using rainfall simulations to understand the relationship between precipitation, soil crust and infiltration in four agricultural soils

NASA Astrophysics Data System (ADS)

Angulo-Martinez, Marta; Alastrué, Juan; Moret-Fernández, David; Beguería, Santiago; López, Mariví; Navas, Ana

2017-04-01

Rainfall simulation experiments were carried out in order to study soil crust formation and its relation with soil infiltration parameters—sorptivity (S) and hydraulic conductivity (K)—on four common agricultural soils with contrasted properties; namely, Cambisol, Gypsisol, Solonchak, and Solonetz. Three different rainfall simulations, replicated three times each of them, were performed over the soils. Prior to rainfall simulations all soils were mechanically tilled with a rototiller to create similar soil surface conditions and homogeneous soils. Rainfall simulation parameters were monitored in real time by a Thies Laser Precipitation Monitor, allowing a complete characterization of simulated rainfall microphysics (drop size and velocity distributions) and integrated variables (accumulated rainfall, intensity and kinetic energy). Once soils dried after the simulations, soil penetration resistance was measured and soil hydraulic parameters, S and K, were estimated using the disc infiltrometry technique. There was little variation in rainfall parameters among simulations. Mean intensity and mean median diameter (D50) varied in simulations 1 ( 0.5 bar), 2 ( 0.8 bar) and 3 ( 1.2 bar) from 26.5 mm h-1 and 0.43 mm (s1) to 40.5 mm h-1 and 0.54 mm (s2) and 41.1 mm h-1 and 0.56 mm for (s3), respectively. Crust formation by soil was explained by D50 and subsequently by the total precipitation amount and the percentage of silt and clay in soil, being Cambisol and Gypsisol the soils that showed more increase in penetration resistance by simulation. All soils showed similar S values by simulations which were explained by rainfall intensity. Different patterns of K were shown by the four soils, which were explained by the combined effect of D50 and intensity, together with soil physico-chemical properties. This study highlights the importance of monitoring all precipitation parameters to determine their effect on different soil processes.

Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature

NASA Astrophysics Data System (ADS)

Hassan, Zulkarnain; Shamsudin, Supiah; Harun, Sobri

2014-04-01

Climate change is believed to have significant impacts on the water basin and region, such as in a runoff and hydrological system. However, impact studies on the water basin and region are difficult, since general circulation models (GCMs), which are widely used to simulate future climate scenarios, do not provide reliable hours of daily series rainfall and temperature for hydrological modeling. There is a technique named as "downscaling techniques", which can derive reliable hour of daily series rainfall and temperature due to climate scenarios from the GCMs output. In this study, statistical downscaling models are used to generate the possible future values of local meteorological variables such as rainfall and temperature in the selected stations in Peninsular of Malaysia. The models are: (1) statistical downscaling model (SDSM) that utilized the regression models and stochastic weather generators and (2) Long Ashton research station weather generator (LARS-WG) that only utilized the stochastic weather generators. The LARS-WG and SDSM models obviously are feasible methods to be used as tools in quantifying effects of climate change condition in a local scale. SDSM yields a better performance compared to LARS-WG, except SDSM is slightly underestimated for the wet and dry spell lengths. Although both models do not provide identical results, the time series generated by both methods indicate a general increasing trend in the mean daily temperature values. Meanwhile, the trend of the daily rainfall is not similar to each other, with SDSM giving a relatively higher change of annual rainfall compared to LARS-WG.

The Effects Of Urban Landscape Patterns On Rainfall-Runoff Processes At Small Scale

NASA Astrophysics Data System (ADS)

Chen, L.

2016-12-01

Many studies have indicated that urban landscape change may alter rainfall-runoff processes. However, how urban landscape pattern affect this process is little addressed. In this study, the hydrological effects of landscape pattern on rainfall-runoff processes at small-scale was explored. Twelve residential blocks with independent drainage systems in Beijing were selected as case study areas. Impervious metrics of these blocks, i.e., total impervious area (TIA) and directly connected impervious area (DCIA), were identified. A drainage index describing catchment general drainage load and the overland flow distance, Ad, was estimated and used as one of the landscape spatial metrics. Three scenarios were designed to test the potential influence of impervious surface pattern on runoff processes. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated under different rainfall conditions by Storm Water Management Model (SWMM). The relationship between landscape patterns and runoff variables were analyzed, and further among the three scenarios. The results demonstrated that, in small urban blocks, spatial patterns have inherent influences on rainfall-runoff processes. Specifically, (1) Imperviousness acts as effective indicators in predicting both Qt and Qp. As rainfall intensity increases, the major affecting factor changes from DCIA to TIA for both Qt and Qp; (2) Increasing the size of drainage area dominated by each drainage inlet will benefit the block peak flow mitigation; (3) Different spatial concentrations of impervious surfaces have inherent influences on Qp, when impervious surfaces located away from the outlet can reduce the peak flow discharge. These findings may provide insights into the role of urban landscape patterns in driving rainfall-runoff responses in urbanization, which is essential for urban planning and stormwater management.

Tree-Ring Reconstruction of Wet Season Rainfall Totals in the Amazon

NASA Astrophysics Data System (ADS)

Stahle, D. W.; Lopez, L.; Granato-Souza, D.; Barbosa, A. C. M. C.; Torbenson, M.; Villalba, R.; Pereira, G. D. A.; Feng, S.; Schongart, J.; Cook, E. R.

2017-12-01

The Amazon Basin is a globally important center of deep atmospheric convection, energy balance, and biodiversity, but only a handful of weather stations in this vast Basin have recorded rainfall measurements for at least 50 years. The available rainfall and river level observations suggest that the hydrologic cycle in the Amazon may have become amplified in the last 40-years, with more extreme rainfall and streamflow seasonality, deeper droughts, and more severe flooding. These changes in the largest hydrological system on earth may be early evidence of the expected consequences of anthropogenic climate change and deforestation in the coming century. Placing these observed and simulated changes in the context of natural climate variability during the late Holocene is a significant challenge for high-resolution paleoclimatology. We have developed exactly dated and well-replicated annual tree-ring chronologies from two native Amazonian tree species (Cedrela sp and Centrolobium microchaete). These moisture sensitive chronologies have been used to compute two reconstructions of wet season rainfall totals, one in the southern Amazon based on Centrolobium and another in the eastern equatorial Amazon using Cedrela. Both reconstructions are over 200-years long and extend the available instrumental observations in each region by over 150-years. These reconstructions are well correlated with the same regional and large-scale climate dynamics that govern the inter-annual variability of the instrumental wet season rainfall totals. Increased multi-decadal variability is reconstructed after 1950 with the Centrolobium chronologies in the southern Amazon. The Cedrela reconstruction from the eastern Amazon exhibits changes in the spatial pattern of correlation with regional rainfall stations and the large-scale sea surface temperature field after 1990 that may be consistent with recent changes in the mean position of the Inter-Tropical Convergence Zone in March over the western Atlantic and South American sector.

Assessing Possible Anthropogenic Contributions to the Rainfall Extremes Associated with Typhoon Morakot (2009)

NASA Astrophysics Data System (ADS)

Chen, C. T.; Lo, S. H.; Wang, C. C.

2014-12-01

More than 2000 mm rainfall occurred over southern Taiwan when a category 1 Typhoon Morakot pass through Taiwan in early August 2009. Entire village and hundred of people were buried by massive mudslides induced by record-breaking precipitation. Whether the past anthropogenic warming played a significant role in such extreme event remained very controversial. On one hand, people argue it's nearly impossible to attribute an individual extreme event to global warming. On the other hand, the increase of heavy rainfall is consistent with the expected effects of climate change on tropical cyclone. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall associated with Typhoon Morakot, we adapt an existing event attribution framework of modeling a 'world that was' and comparing it to a modeled 'world that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. One limitation for applying such approach to high-impact weather system is that it will require models capable of capturing the essential processes lead to the studied extremes. Using a cloud system resolving model that can properly simulate the complicated interactions between tropical cyclone, large-scale background, topography, we first perform the ensemble 'world that was' simulations using high resolution ECMWF YOTC analysis. We then re-simulate, having adjusted the analysis to 'world that might have been conditions' by removing the regional atmospheric and oceanic forcing due to human influences estimated from the CMIP5 model ensemble mean conditions between all forcing and natural forcing only historical runs. Thus our findings are highly conditional on the driving analysis and adjustments therein, but the setup allows us to elucidate possible contribution of anthropogenic forcing to changes in the likelihood of heavy rainfall associated Typhoon Morakot in early August 2009.

Combining spray nozzle simulators with meshes: characterization of rainfall intensity and drop properties

NASA Astrophysics Data System (ADS)

Carvalho, Sílvia C. P.; de Lima, João L. M. P.; de Lima, M. Isabel P.

2013-04-01

Rainfall simulators can be a powerful tool to increase our understanding of hydrological and geomorphological processes. Nevertheless, rainfall simulators' design and operation might be rather demanding, for achieving specific rainfall intensity distributions and drop characteristics. The pressurized simulators have some advantages over the non-pressurized simulators: drops do not rely on gravity to reach terminal velocity, but are sprayed out under pressure; pressurized simulators also yield a broad range of drop sizes in comparison with drop-formers simulators. The main purpose of this study was to explore in the laboratory the potential of combining spray nozzle simulators with meshes in order to change rainfall characteristics (rainfall intensity and diameters and fall speed of drops). Different types of spray nozzles were tested, such as single full-cone and multiple full-cone nozzles. The impact of the meshes on the simulated rain was studied by testing different materials (i.e. plastic and steel meshes), square apertures and wire thicknesses, and different vertical distances between the nozzle and the meshes underneath. The diameter and fall speed of the rain drops were measured using a Laser Precipitation Monitor (Thies Clima). The rainfall intensity range and coefficients of uniformity of the sprays and the drop size distribution, fall speed and kinetic energy were analysed. Results show that when meshes intercept drop trajectories the spatial distribution of rainfall intensity and the drop size distribution are affected. As the spray nozzles generate typically small drop sizes and narrow drop size distributions, meshes can be used to promote the formation of bigger drops and random their landing positions.

Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

NASA Astrophysics Data System (ADS)

Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

2016-05-01

Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

Sensitivity of peak flow to the change of rainfall temporal pattern due to warmer climate

NASA Astrophysics Data System (ADS)

Fadhel, Sherien; Rico-Ramirez, Miguel Angel; Han, Dawei

2018-05-01

The widely used design storms in urban drainage networks has different drawbacks. One of them is that the shape of the rainfall temporal pattern is fixed regardless of climate change. However, previous studies have shown that the temporal pattern may scale with temperature due to climate change, which consequently affects peak flow. Thus, in addition to the scaling of the rainfall volume, the scaling relationship for the rainfall temporal pattern with temperature needs to be investigated by deriving the scaling values for each fraction within storm events, which is lacking in many parts of the world including the UK. Therefore, this study analysed rainfall data from 28 gauges close to the study area with a 15-min resolution as well as the daily temperature data. It was found that, at warmer temperatures, the rainfall temporal pattern becomes less uniform, with more intensive peak rainfall during higher intensive times and weaker rainfall during less intensive times. This is the case for storms with and without seasonal separations. In addition, the scaling values for both the rainfall volume and the rainfall fractions (i.e. each segment of rainfall temporal pattern) for the summer season were found to be higher than the corresponding results for the winter season. Applying the derived scaling values for the temporal pattern of the summer season in a hydrodynamic sewer network model produced high percentage change of peak flow between the current and future climate. This study on the scaling of rainfall fractions is the first in the UK, and its findings are of importance to modellers and designers of sewer systems because it can provide more robust scenarios for flooding mitigation in urban areas.

Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

NASA Astrophysics Data System (ADS)

Bal, Prasanta Kumar; Ramachandran, A.; Geetha, R.; Bhaskaran, B.; Thirumurugan, P.; Indumathi, J.; Jayanthi, N.

2016-02-01

In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments.

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

NASA Astrophysics Data System (ADS)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial variability of precipitation will help in the planning and management of the built environment more efficiently.

Atmospheric electricity/meteorology analysis

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard; Buechler, Dennis

1993-01-01

This activity focuses on Lightning Imaging Sensor (LIS)/Lightning Mapper Sensor (LMS) algorithm development and applied research. Specifically we are exploring the relationships between (1) global and regional lightning activity and rainfall, and (2) storm electrical development, physics, and the role of the environment. U.S. composite radar-rainfall maps and ground strike lightning maps are used to understand lightning-rainfall relationships at the regional scale. These observations are then compared to SSM/I brightness temperatures to simulate LIS/TRMM multi-sensor algorithm data sets. These data sets are supplied to the WETNET project archive. WSR88-D (NEXRAD) data are also used as it becomes available. The results of this study allow us to examine the information content from lightning imaging sensors in low-earth and geostationary orbits. Analysis of tropical and U.S. data sets continues. A neural network/sensor fusion algorithm is being refined for objectively associating lightning and rainfall with their parent storm systems. Total lightning data from interferometers are being used in conjunction with data from the national lightning network. A 6-year lightning/rainfall climatology has been assembled for LIS sampling studies.

Stochastic extreme downscaling model for an assessment of changes in rainfall intensity-duration-frequency curves over South Korea using multiple regional climate models

NASA Astrophysics Data System (ADS)

So, Byung-Jin; Kim, Jin-Young; Kwon, Hyun-Han; Lima, Carlos H. R.

2017-10-01

A conditional copula function based downscaling model in a fully Bayesian framework is developed in this study to evaluate future changes in intensity-duration frequency (IDF) curves in South Korea. The model incorporates a quantile mapping approach for bias correction while integrated Bayesian inference allows accounting for parameter uncertainties. The proposed approach is used to temporally downscale expected changes in daily rainfall, inferred from multiple CORDEX-RCMs based on Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios, into sub-daily temporal scales. Among the CORDEX-RCMs, a noticeable increase in rainfall intensity is observed in the HadGem3-RA (9%), RegCM (28%), and SNU_WRF (13%) on average, whereas no noticeable changes are observed in the GRIMs (-2%) for the period 2020-2050. More specifically, a 5-30% increase in rainfall intensity is expected in all of the CORDEX-RCMs for 50-year return values under the RCP 8.5 scenario. Uncertainty in simulated rainfall intensity gradually decreases toward the longer durations, which is largely associated with the enhanced strength of the relationship with the 24-h annual maximum rainfalls (AMRs). A primary advantage of the proposed model is that projected changes in future rainfall intensities are well preserved.

Mechanism of ENSO influence on the South Asian monsoon rainfall in global model simulations

NASA Astrophysics Data System (ADS)

Joshi, Sneh; Kar, Sarat C.

2018-02-01

Coupled ocean atmosphere global climate models are increasingly being used for seasonal scale simulation of the South Asian monsoon. In these models, sea surface temperatures (SSTs) evolve as coupled air-sea interaction process. However, sensitivity experiments with various SST forcing can only be done in an atmosphere-only model. In this study, the Global Forecast System (GFS) model at T126 horizontal resolution has been used to examine the mechanism of El Niño-Southern Oscillation (ENSO) forcing on the monsoon circulation and rainfall. The model has been integrated (ensemble) with observed, climatological and ENSO SST forcing to document the mechanism on how the South Asian monsoon responds to basin-wide SST variations in the Indian and Pacific Oceans. The model simulations indicate that the internal variability gets modulated by the SSTs with warming in the Pacific enhancing the ensemble spread over the monsoon region as compared to cooling conditions. Anomalous easterly wind anomalies cover the Indian region both at 850 and 200 hPa levels during El Niño years. The locations and intensity of Walker and Hadley circulations are altered due to ENSO SST forcing. These lead to reduction of monsoon rainfall over most parts of India during El Niño events compared to La Niña conditions. However, internally generated variability is a major source of uncertainty in the model-simulated climate.

Improve projections of changes in southern African summer rainfall through comprehensive multi-timescale empirical statistical downscaling

NASA Astrophysics Data System (ADS)

Dieppois, B.; Pohl, B.; Eden, J.; Crétat, J.; Rouault, M.; Keenlyside, N.; New, M. G.

2017-12-01

The water management community has hitherto neglected or underestimated many of the uncertainties in climate impact scenarios, in particular, uncertainties associated with decadal climate variability. Uncertainty in the state-of-the-art global climate models (GCMs) is time-scale-dependant, e.g. stronger at decadal than at interannual timescales, in response to the different parameterizations and to internal climate variability. In addition, non-stationarity in statistical downscaling is widely recognized as a key problem, in which time-scale dependency of predictors plays an important role. As with global climate modelling, therefore, the selection of downscaling methods must proceed with caution to avoid unintended consequences of over-correcting the noise in GCMs (e.g. interpreting internal climate variability as a model bias). GCM outputs from the Coupled Model Intercomparison Project 5 (CMIP5) have therefore first been selected based on their ability to reproduce southern African summer rainfall variability and their teleconnections with Pacific sea-surface temperature across the dominant timescales. In observations, southern African summer rainfall has recently been shown to exhibit significant periodicities at the interannual timescale (2-8 years), quasi-decadal (8-13 years) and inter-decadal (15-28 years) timescales, which can be interpret as the signature of ENSO, the IPO, and the PDO over the region. Most of CMIP5 GCMs underestimate southern African summer rainfall variability and their teleconnections with Pacific SSTs at these three timescales. In addition, according to a more in-depth analysis of historical and pi-control runs, this bias is might result from internal climate variability in some of the CMIP5 GCMs, suggesting potential for bias-corrected prediction based empirical statistical downscaling. A multi-timescale regression based downscaling procedure, which determines the predictors across the different timescales, has thus been used to simulate southern African summer rainfall. This multi-timescale procedure shows much better skills in simulating decadal timescales of variability compared to commonly used statistical downscaling approaches.

An experimental method to verify soil conservation by check dams on the Loess Plateau, China.

PubMed

Xu, X Z; Zhang, H W; Wang, G Q; Chen, S C; Dang, W Q

2009-12-01

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model-prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D(a) and D(b), have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.

Using SMAP Data to Investigate the Role of Soil Moisture Variability on Realtime Flood Forecasting

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Jadidoleslam, N.; Mantilla, R.

2017-12-01

The Iowa Flood Center has developed a regional high-resolution flood-forecasting model for the state of Iowa that decomposes the landscape into hillslopes of about 0.1 km2. For the model to benefit, through data assimilation, from SMAP observations of soil moisture (SM) at scales of approximately 100 km2, we are testing a framework to connect SMAP-scale observations to the small-scale SM variability calculated by our rainfall-runoff models. As a step in this direction, we performed data analyses of 15-min point SM observations using a network of about 30 TDR instruments spread throughout the state. We developed a stochastic point-scale SM model that captures 1) SM increases due to rainfall inputs, and 2) SM decay during dry periods. We use a power law model to describe soil moisture decay during dry periods, and a single parameter logistic curve to describe precipitation feedback on soil moisture. We find that the parameters of the models behave as time-independent random variables with stationary distributions. Using data-based simulation, we explore differences in the dynamical range of variability of hillslope and SMAP-scale domains. The simulations allow us to predict the runoff field and streamflow hydrographs for the state of Iowa during the three largest flooding periods (2008, 2014, and 2016). We also use the results to determine the reduction in forecast uncertainty from assimilation of unbiased SMAP-scale soil moisture observations.

Origins and interrelationship of Intraseasonal rainfall variations around the Maritime Continent during boreal winter

NASA Astrophysics Data System (ADS)

Cao, Xi; Wu, Renguang

2018-04-01

Large intraseasonal rainfall variations are identified over the southern South China Sea (SSCS), tropical southeastern Indian Ocean (SEIO), and east coast of the Philippines (EPHI) in boreal winter. The present study contrasts origins and propagations and investigates interrelations of intraseasonal rainfall variations on the 10-20- and 30-60-day time scales in these regions. Different origins are identified for intraseasonal rainfall anomalies over the SSCS, SEIO, and EPHI on both time scales. On the 10-20-day time scale, strong northerly or northeasterly wind anomalies related to the East Asian winter monsoon (EAWM) play a major role in intraseasonal rainfall variations over the SSCS and EPHI. On the 30-60-day time scale, both the intraseasonal signal from the tropical Indian Ocean and the EAWM-related wind anomalies contribute to intraseasonal rainfall variations over the SSCS, whereas the EAWM-related wind anomalies have a major contribution to the intraseasonal rainfall variations over the EPHI. No relation is detected between the intraseasonal rainfall variations over the SEIO and the EAWM on both the 10-20-day and 30-60-day time scales. The anomalies associated with intraseasonal rainfall variations over the SSCS and EPHI propagate northwestward and northeastward, respectively, on the 10-20- and 30-60-day time scales. The intraseasonal rainfall anomalies display northwestward and northward propagation over the Bay of Bengal, respectively, on the 10-20- and 30-60-day time scales.

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

NASA Astrophysics Data System (ADS)

Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

2017-04-01

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this research. Hopefully, all results developed from this research can be used as a warning system for Predicting Large Scale Landslides in the southern Taiwan. Keywords：Heavy Rainfall, Large Scale, landslides, Critical Rainfall Value

Rainfall Data Simulation

Treesearch

T.L. Rogerson

1980-01-01

A simple simulation model to predict rainfall for individual storms in central Arkansas is described. Output includes frequency distribution tables for days between storms and for storm size classes; a storm summary by day number (January 1 = 1 and December 31 = 365) and rainfall amount; and an annual storm summary that includes monthly values for rainfall and number...

Radar-rain-gauge rainfall estimation for hydrological applications in small catchments

NASA Astrophysics Data System (ADS)

Gabriele, Salvatore; Chiaravalloti, Francesco; Procopio, Antonio

2017-07-01

The accurate evaluation of the precipitation's time-spatial structure is a critical step for rainfall-runoff modelling. Particularly for small catchments, the variability of rainfall can lead to mismatched results. Large errors in flow evaluation may occur during convective storms, responsible for most of the flash floods in small catchments in the Mediterranean area. During such events, we may expect large spatial and temporal variability. Therefore, using rain-gauge measurements only can be insufficient in order to adequately depict extreme rainfall events. In this work, a double-level information approach, based on rain gauges and weather radar measurements, is used to improve areal rainfall estimations for hydrological applications. In order to highlight the effect that precipitation fields with different level of spatial details have on hydrological modelling, two kinds of spatial rainfall fields were computed for precipitation data collected during 2015, considering both rain gauges only and their merging with radar information. The differences produced by these two precipitation fields in the computation of the areal mean rainfall accumulation were evaluated considering 999 basins of the region Calabria, southern Italy. Moreover, both of the two precipitation fields were used to carry out rainfall-runoff simulations at catchment scale for main precipitation events that occurred during 2015 and the differences between the scenarios obtained in the two cases were analysed. A representative case study is presented in detail.

Use of Regional Climate Model Output for Hydrologic Simulations

NASA Astrophysics Data System (ADS)

Hay, L. E.; Clark, M. P.; Wilby, R. L.; Gutowski, W. J.; Leavesley, G. H.; Pan, Z.; Arritt, R. W.; Takle, E. S.

2001-12-01

Daily precipitation and maximum and minimum temperature time series from a Regional Climate Model (RegCM2) were used as input to a distributed hydrologic model for a rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango, Colorado; East Fork of the Carson River near Gardnerville, Nevada; and Cle Elum River near Roslyn, Washington). For comparison purposes, spatially averaged daily data sets of precipitation and maximum and minimum temperature were developed from measured data. These datasets included precipitation and temperature data for all stations that are located within the area of the RegCM2 model output used for each basin, but excluded station data used to calibrate the hydrologic model. Both the RegCM2 output and station data capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all four basins, the RegCM2- and station-based simulations of runoff show little skill on a daily basis (Nash-Sutcliffe (NS) values ranging from 0.05-0.37 for RegCM2 and -0.08-0.65 for station). When the precipitation and temperature biases are corrected in the RegCM2 output and station data sets (Bias-RegCM2 and Bias-station, respectively) the accuracy of the daily runoff simulations improve dramatically for the snowmelt-dominated basins. In the rainfall-dominated basin, runoff simulations based on the Bias-RegCM2 output show no skill (NS value of 0.09) whereas Bias-All simulated runoff improves (NS value improved from -0.08 to 0.72). These results indicate that the resolution of the RegCM2 output is appropriate for basin-scale modeling, but RegCM2 model output does not contain the day-to-day variability needed for basin-scale modeling in rainfall-dominated basins. Future work is warranted to identify the causes for systematic biases in RegCM2 simulations, develop methods to remove the biases, and improve RegCM2 simulations of daily variability in local climate.

Nonlinear responses of southern African rainfall to forcing from Atlantic SST in a high-resolution regional climate model

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, high resolution satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA) are used as a basis for undertaking model experiments using a state-of-the-art regional climate model. The MIRA dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the regional climate model's domain size are briefly presented, before a comparison of simulated daily rainfall from the model with the satellite-derived dataset. Secondly, simulations of current climate and rainfall extremes from the model are compared to the MIRA dataset at daily timescales. Finally, the results from the idealised SST experiments are presented, suggesting highly nonlinear associations between rainfall extremes remote SST anomalies.

Effects of Raindrop Shape Parameter on the Simulation of Plum Rains

NASA Astrophysics Data System (ADS)

Mei, H.; Zhou, L.; Li, X.; Huang, X.; Guo, W.

2017-12-01

The raindrop shape parameter of particle distribution is generally set as constant in a Double-moment Bulk Microphysics Scheme (DBMS) using Gama distribution function though which suggest huge differences in time and space according to observations. Based on Milbrandt 2-mon(MY) DBMS, four cases during Plum Rains season are simulated coupled with four empirical relationships between shape parameter (μr) and slope parameter of raindrop which have been concluded from observations of raindrop distributions. The analysis of model results suggest that μr have some influences on rainfall. Introducing the diagnostic formulas of μr may have some improvement on systematic biases of 24h accumulated rainfall and show some correction ability on local characteristics of rainfall distribution. Besides,the tendency to improve strong rainfall could be sensitive to μr. With the improvement of the diagnosis of μr using the empirically diagnostic formulas, μr increases generally in the middle- and lower-troposphere and decreases with the stronger rainfall. Its conclued that, the decline in raindrop water content and the increased raindrop mass-weighted average terminal velocity directly related to μr are the direct reasons of variations in the precipitation.On the other side, the environmental conditions including relative humidity and dynamical parameters are the key indirectly causes which has close relationships with the changes in cloud particles and rainfall distributions.Furthermore,the differences in the scale of improvement between the weak and heavy rainfall mainly come from the distinctions of response features about their variable fields respectively. The extent of variation in the features of cloud particles in warm clouds of heavy rainfall differs greatly from that of weak rainfall, though they share the same trend of variation. On the conditions of weak rainfall, the response of physical characteristics to μr performed consistent trends and some linear features. However, environmental conditions of relative humidity and dynamical parameters perform strong and vertically deep adjustments in the heavy precipitation with vigorous cloud systems. In this case, the microphysical processes and environmental conditions experience complex interactions with each other and no significant laws could be concluded.

A Spatial Perspective of Droughts and Pluvials in the Tropics and their Relationships to ENSO in CMIP5 Model Simulations

NASA Astrophysics Data System (ADS)

Perez Arango, J. D.; Lintner, B. R.; Lyon, B.

2016-12-01

Although many aspects of the tropical response to ENSO are well-known, the spatial characteristics of the rainfall response to ENSO remain relatively unexplored. Moreover, in current generation climate models, the spatial signatures of the ENSO tropical teleconnection are more uncertain than other aspects of ENSO variability, such as the amplitude of rainfall anomalies. Following the approach of Lyon (2004) and Lyon and Barnston (2005), we analyze here integrated measures of the spatial extent of drought and pluvial conditions in the tropics and their relationship to ENSO in observations as well as simulations of Phase 5 of the Coupled Model Intercomparison Project (CMIP5) with prescribed SST forcing. We compute diagnostics including the model ensemble-means and standard deviations of moderate, intermediate, and severe droughts and pluvials and the lagged correlations with respect to ENSO-based SST indices like NINO3. Overall, in a tropics-wide sense, the models generally capture the areal extent of observed droughts and pluvials and their phasing with respect to ENSO. However, at more local scales, e.g., tropical South America, the simulated metrics agree less strongly with observations, underscoring the role of errors in the spatial patterns of ENSO-induced rainfall anomalies.

A Method for Partitioning Surface and Subsurface Flow Using Rainfall Simulaton and Two-Dimensional Surface Electrical Resistivity Imaging

NASA Astrophysics Data System (ADS)

Carey, A. M.; Paige, G. B.; Miller, S. N.; Carr, B. J.; Holbrook, W. S.

2014-12-01

In semi-arid rangeland environments understanding how surface and subsurface flow processes and their interactions are influenced by watershed and rainfall characteristics is critical. However, it is difficult to resolve the temporal variations between mechanisms controlling these processes and challenging to obtain field measurements that document their interactions. Better insight into how these complex systems respond hydrologically is necessary in order to refine hydrologic models and decision support tools. We are conducting field studies integrating high resolution, two-dimensional surface electrical resistivity imaging (ERI) with variable intensity rainfall simulation, to quantify real-time partitioning of rainfall into surface and subsurface response. These studies are being conducted at the hillslope scale on long-term runoff plots on four different ecological sites in the Upper Crow Creek Watershed in southeastern Wyoming. Variable intensity rainfall rates were applied using the Walnut Gulch Rainfall Simulator in which intensities were increased incrementally from 49 to 180 mm hr-1 and steady-state runoff rates for each intensity were measured. Two 13.5 m electrode arrays at 0.5 m spacing were positioned on the surface perpendicular to each plot and potentials were measured at given time intervals prior to, during and following simulations using a dipole-dipole array configuration. The configuration allows for a 2.47 m depth of investigation in which magnitude and direction of subsurface flux can be determined. We used the calculated steady state infiltration rates to quantify the variability in the partial area runoff response on the ecological sites. Coupling this information with time-lapse difference inversions of ERI data, we are able to track areas of increasing and decreasing resistivity in the subsurface related to localized areas of infiltration during and following rainfall events. We anticipate implementing this method across a variety of ecological sites in the Upper Crow Creek in order to characterize the variable hydrologic response of this complex rangeland watershed. This information is being used to refine current physically based hydrologic models and watershed assessment tools.

Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.

Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over centralmore » India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. Lastly, it is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate.« less

Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

DOE PAGES

Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.; ...

2016-05-10

Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over centralmore » India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. Lastly, it is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate.« less

Data assimilation experiment of precipitable water vapor observed by a hyper-dense GNSS receiver network using a nested NHM-LETKF system

NASA Astrophysics Data System (ADS)

Oigawa, Masanori; Tsuda, Toshitaka; Seko, Hiromu; Shoji, Yoshinori; Realini, Eugenio

2018-05-01

We studied the assimilation of high-resolution precipitable water vapor (PWV) data derived from a hyper-dense global navigation satellite system network around Uji city, Kyoto, Japan, which had a mean inter-station distance of about 1.7 km. We focused on a heavy rainfall event that occurred on August 13-14, 2012, around Uji city. We employed a local ensemble transform Kalman filter as the data assimilation method. The inhomogeneity of the observed PWV increased on a scale of less than 10 km in advance of the actual rainfall detected by the rain gauge. Zenith wet delay data observed by the Uji network showed that the characteristic length scale of water vapor distribution during the rainfall ranged from 1.9 to 3.5 km. It is suggested that the assimilation of PWV data with high horizontal resolution (a few km) improves the forecast accuracy. We conducted the assimilation experiment of high-resolution PWV data, using both small horizontal localization radii and a conventional horizontal localization radius. We repeated the sensitivity experiment, changing the mean horizontal spacing of the PWV data from 1.7 to 8.0 km. When the horizontal spacing of assimilated PWV data was decreased from 8.0 to 3.5 km, the accuracy of the simulated hourly rainfall amount worsened in the experiment that used the conventional localization radius for the assimilation of PWV. In contrast, the accuracy of hourly rainfall amounts improved when we applied small horizontal localization radii. In the experiment that used the small horizontal localization radii, the accuracy of the hourly rainfall amount was most improved when the horizontal resolution of the assimilated PWV data was 3.5 km. The optimum spatial resolution of PWV data was related to the characteristic length scale of water vapor variability.[Figure not available: see fulltext.

Toward Characterizing the 4D Structure of Precipitation at the Headwater Catchment Scale in Mountainous Regions

NASA Astrophysics Data System (ADS)

Barros, A. P.; Prat, O. P.; Sun, X.; Shrestha, P.; Miller, D.

2009-04-01

The classic conceptual model of orographic rainfall depicts strong stationary horizontal gradients in rainfall accumulations and landcover contrasts across topographic divides (i.e. the rainshadow) at the broad scale of mountain ranges, or isolated orographic features. Whereas this model is sufficient to fingerprint the land-modulation of precipitation at the macroscale in climate studies, and can be useful to force geological models of land evolution for example, it fails to describe the active 4D space-time gradients that are critical at the fundamental scale of mountain hydrometeorology and hydrology, that is the headwater catchment. That is, the scale at which flash-floods are generated and landslides are triggered. Our work surveying the spatial and temporal habits of clouds and rainfall for some of the world's major mountain ranges from remotely-sensed data shows a close alignment of spatial scaling behavior with landform down to the mountain fold scale, that is the ridge-valley. Likewise, we find that diurnal and seasonal cycles are organized and constrained by topography from the macro- to the meso- to the alpha-scale of individual basins varying with synoptic weather conditions. At the catchment scale, the diurnal cycle exhibits an oscillatory behavior with storm features moving up and down from the ridge crests to the valley floor and back and forth from head to mouth along the valley with strong variations in rainfall intensity and duration. Direct observations to provide quantitative estimates of precipitation at this scale are beyond the capability of satellite-based observations present and anticipated in the next 10-20 years. This limitation can be addressed by assimilating the space-time modes of variability of rainfall into satellite-observations at coarser scale using multiscale blending algorithms. The challenge is to characterize the modes of space-time variability of precipitation in a systematic, and quantitative fashion that can be generalized. It requires understanding the physical controls that govern the diurnal cycle and how these physical controls translate into spatial and temporal variability of dynamics and microphysics of precipitation in headwater catchments, and especially in the context of extreme events for natural hazards assessments. Toward this goal, we have initiated a sequence of number of intense observing period (IOP) campaigns in the Great Smoky Mountains National Park using radiosondes, tethersondes, microrain radars, and a high resolution raingauge network that for the first time monitors rainfall systematically along ridges in the Appalachians. Along with field observations, a high-resolution coupled model has been implemented to diagnose the evolution of the 4D structure of regional circulations and associated precipitation for IOP conditions and for reconstructing historical extremes associated with the interaction of tropical cyclones with the mountains. A synthesis of data analysis and model simulations will be presented.

A single scaling parameter as a first approximation to describe the rainfall pattern of a place: application on Catalonia

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Llabrés-Brustenga, Alba; Rius, Anna; Rodríguez-Solà, Raúl; Navarro, Xavier

2018-02-01

As well as in other natural processes, it has been frequently observed that the phenomenon arising from the rainfall generation process presents fractal self-similarity of statistical type, and thus, rainfall series generally show scaling properties. Based on this fact, there is a methodology, simple scaling, which is used quite broadly to find or reproduce the intensity-duration-frequency curves of a place. In the present work, the relationship of the simple scaling parameter with the characteristic rainfall pattern of the area of study has been investigated. The calculation of this scaling parameter has been performed from 147 daily rainfall selected series covering the temporal period between 1883 and 2016 over the Catalonian territory (Spain) and its nearby surroundings, and a discussion about the relationship between the scaling parameter spatial distribution and rainfall pattern, as well as about trends of this scaling parameter over the past decades possibly due to climate change, has been presented.

Temporal rainfall estimation using input data reduction and model inversion

NASA Astrophysics Data System (ADS)

Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

2016-12-01

Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a demonstration of equifinality. The use of a likelihood function that considers both rainfall and streamflow error combined with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

Characterizing multiscale variability of zero intermittency in spatial rainfall

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1994-01-01

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

Round versus rectangular: Does the plot shape matter?

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Bäthke, Lars; Ries, Johannes B.

2016-04-01

Field rainfall simulators are designed to study soil erosion processes and provide urgently needed data for various geomorphological, hydrological and pedological issues. Due to the different conditions and technologies applied, there are several methodological aspects under review of the scientific community, particularly concerning design, procedures and conditions of measurement for infiltration, runoff and soil erosion. Extensive discussions at the Rainfall Simulator Workshop 2011 in Trier and the Splinter Meeting at EGU 2013 "Rainfall simulation: Big steps forward!" lead to the opinion that the rectangular shape is the more suitable plot shape compared to the round plot. A horizontally edging Gerlach trough is installed for sample collection without forming unnatural necks as is found at round or triangle plots. Since most research groups did and currently do work with round plots at the point scale (<1m²), a precise analysis of the differences between the output of round and square plots are necessary. Our hypotheses are: - Round plot shapes disturb surface runoff, unnatural fluvial dynamics for the given plot size such as pool development especially directly at the plot's outlet occur. - A square plot shape prevent these problems. A first comparison between round and rectangular plots (Iserloh et al., 2015) indicates that the rectangular plot could indeed be the more suitable, but the rather ambiguous results make a more elaborate test setup necessary. The laboratory test setup includes the two plot shapes (round, square), a standardised silty substrate and three inclinations (2°, 6°, 12°). The analysis of the laboratory test provide results on the best performance concerning undisturbed surface runoff and soil/water sampling at the plot's outlet. The analysis of the plot shape concerning its influence on runoff and erosion shows that clear methodological standards are necessary in order to make rainfall simulation experiments comparable. Reference: Iserloh, T., Pegoraro, D., Schlösser, A., Thesing, H., Seeger, M., Ries, J.B. (2015): Rainfall simulation experiments: Influence of water temperature, water quality and plot design on soil erosion and runoff. Geophysical Research Abstracts, Vol. 17, EGU2015-5817.

On the estimate of the Vegetation effects on the surface runoff through a plot scale rainfall simulator in Sardinia, Italy.

NASA Astrophysics Data System (ADS)

Corona, R.; Montaldo, N.; Cortis, C.; Albertson, J. D.

2012-04-01

In semi-arid regions with the Mediterranean climate of cool, wet winters and hot, dry summers, precipitation timing and amount, vegetation growth, and surface runoff are tightly intertwined. In the experimental site of Sardinia, the main source of water is surface reservoirs that are recharged by surface runoff in the rainy winter season. However, changes in climate are expected to bring both an overall decrease in winter precipitation and increased interannual variability of precipitation to this region. These changes may affect characteristics of the water-limited vegetation growth such as timing and production, and consequently change the amount of overland flow and reservoir recharge. Currently, there is little research on the combination of these effects; therefore, the goal of this research is to assess the runoff response of the land surface with varying vegetation states to ultimately predict how changes in the climate of Mediterranean watersheds may affect the needs of water resource management. A 4 m by 4 m rainfall simulator was designed, constructed, and tested as the first stage of this research. The rainfall simulator consisted of four independent lines of low-cost pressure washing nozzles operated at a pressure of 80 mbar, with the number of nozzles determining the rainfall intensity delivered to the plot. The rainfall intensity of the simulator varies from approximately 26 to 52 mm/h with a coefficient of uniformity ranging from 0.40 to 0.59. Measurements taken include surface runoff using a tipping bucket flow meter and soil moisture throughout the plot. Literature models for surface runoff predictions (Philips, Horton, Green Ampt, Soil conservation Service model, bucket model) are widely tested highlighting the typical hortonian behavior of this soil. The simulator was used to monitor changes in the surface runoff throughout the seasons (July 2010, August 2010, June 2011, July 2011, December 2011, January 2012) as the vegetation changes. Results shows the great impact of changes in vegetation cover on soil runoff processes: the increase of LAI from values of 0 to 1.5 produces a decrease of surface runoff of the 50%.

Sensitivity of Catchment Transit Times to Rainfall Variability Under Present and Future Climates

NASA Astrophysics Data System (ADS)

Wilusz, Daniel C.; Harman, Ciaran J.; Ball, William P.

2017-12-01

Hydrologists have a relatively good understanding of how rainfall variability shapes the catchment hydrograph, a reflection of the celerity of hydraulic head propagation. Much less is known about the influence of rainfall variability on catchment transit times, a reflection of water velocities that control solute transport. This work uses catchment-scale lumped parameter models to decompose the relationship between rainfall variability and an important metric of transit times, the time-varying fraction of young water (<90 days old) in streams (FYW). A coupled rainfall-runoff model and rank StorAge Selection (rSAS) transit time model were calibrated to extensive hydrometric and environmental tracer data from neighboring headwater catchments in Plynlimon, Wales from 1999 to 2008. At both sites, the mean annual FYW increased more than 13 percentage points from the driest to the wettest year. Yearly mean rainfall explained most between-year variation, but certain signatures of rainfall pattern were also associated with higher FYW including: more clustered storms, more negatively skewed storms, and higher covariance between daily rainfall and discharge. We show that these signatures are symptomatic of an "inverse storage effect" that may be common among watersheds. Looking to the future, changes in rainfall due to projected climate change caused an up to 19 percentage point increase in simulated mean winter FYW and similarly large decreases in the mean summer FYW. Thus, climate change could seasonally alter the ages of water in streams at these sites, with concomitant impacts on water quality.

Influence of Kuroshio Oceanic Eddies on North Pacific Weather Patterns

NASA Astrophysics Data System (ADS)

Ma, X.; Chang, P.; Saravanan, R.; Montuoro, R.; Hsieh, J. S.; Wu, D.; Lin, X.; Wu, L.; Jing, Z.

2016-02-01

High-resolution satellite observations reveal energetic meso-scale ocean eddy activity and positive correlation between meso-scale sea surface temperature (SST) and surface wind along oceanic frontal zones, such as the Kuroshio and Gulf Stream, suggesting a potential role of meso-scale oceanic eddies in forcing the atmosphere. Using a 27 km horizontal resolution Weather Research Forecasting (WRF) model forced with observed daily SST at 0.09° spatial resolution during boreal winter season, two ensembles of 10 WRF simulations, in one of which meso-scale SST variability induced by ocean eddies was suppressed, were conducted in the North Pacific to study the local and remote influence of meso-scale oceanic eddies in the Kuroshio Extention Region (KER) on the atmosphere. Suppression of meso-scale oceanic eddies results in a deep tropospheric response along and downstream of the KER, including a significant decrease (increase) in winter season mean rainfall along the KER (west coast of US), a reduction of storm genesis in the KER, and a southward shift of the jet stream and North Pacific storm track in the eastern North Pacific. The simulated local and remote rainfall response to meso-scale oceanic eddies in the KER is also supported by observational analysis. A mechanism invoking moist baroclinic instability is proposed as a plausible explanation for the linkage between meso-scale oceanic eddies in the KER and large-scale atmospheric response in the North Pacific. It is argued that meso-scale oceanic eddies can have a rectified effect on planetary boundary layer moisture, the stability of the lower atmosphere and latent heat release, which in turn affect cyclogenesis. The accumulated effect of the altered storm development downstream further contributes to the equivalent barotropic mean flow change in the eastern North Pacific basin.

On using TRMM data and rainfall forecasts from meteorological models in data-scarce transboundary catchments - an example of Bangladesh

NASA Astrophysics Data System (ADS)

Bhattacharya, Biswa; Tohidul Islam, Md.

2014-05-01

This research focuses on the flood risk of the Haor region in the north-eastern part of Bangladesh. The prediction of the hydrological variables at different spatial and temporal scales in the Haor region is dependent on the influence of several upstream rivers in the Meghalaya catchment in India. Limitation in hydro-meteorological data collection and data sharing issues between the two countries dominate the feasibility of hydrological studies, particularly for near-realtime predictions. One of the possible solutions seems to be in making use of the variety of satellite based and meteorological model products for rainfall. The abundance of a variety of rainfall products provides a good basis of hydrological modelling of a part of the Ganges and Brahmaputra basin. In this research the TRMM data and rainfall forecasts from ECMWF have been compared with the scarce rain gauge data from the upstream Meghalaya catchment. Subsequently, the TRMM data and rainfall forecasts from ECMWF have been used as the meteorological input to a rainfall-runoff model of the Meghalaya catchment. The rainfall-runoff model of Meghalaya has been developed using the DEM data from SRTM. The generated runoff at the outlet of Meghalaya has been used as the upstream boundary condition in the existing rainfall-runoff model of the Haor region. The simulation results have been compared with the existing results based on simulations without any information of the rainfall-runoff in the upstream Meghalaya catchment. The comparison showed that the forecasting lead time has been substantially increased. As per the existing results the forecasting lead time at a number of locations in the catchment was about 6 to 8 hours. With the new results the forecasting lead time has gone up, with different levels of accuracy, to about 24 hours. This additional lead time will be highly beneficial in managing flood risk of the Haor region of Bangladesh. The research shows that satellite based rainfall products and rainfall forecasts from meteorological models can be very useful in flood risk management, particularly for data scarce regions and/or transboundary regions with data sharing issues. Keywords: flood risk management, TRMM, ECMWF, flood forecasting, Haor, Bangladesh. Abbreviations: TRMM: Tropical Rainfall Measuring Mission ECMWF: European Centre for Medium-Range Weather Forecasts DEM: Digital Elevation Model SRTM: Shuttle Radar Topography Mission

A coupled synoptic-hydrological model for climate change impact assessment

NASA Astrophysics Data System (ADS)

Wilby, Robert; Greenfield, Brian; Glenny, Cathy

1994-01-01

A coupled atmospheric-hydrological model is presented. Sequences of daily rainfall occurrence for the 20 year period 1971-1990 at sites in the British Isles are related to the Lamb's Weather Types (LWT) by using conditional probabilities. Time series of circulation patterns and hence rainfall were then generated using a Markov representation of matrices of transition probabilities between weather types. The resultant precipitation data were used as input to a semidistributed catchment model to simulate daily flows. The combined model successfully reproduced aspects of the daily weather, precipitation and flow regimes. A range of synoptic scenarios were further investigated with particular reference to low flows in the River Coln, UK. The modelling approach represents a means of translating general circulation model (GCM) climate change predictions at the macro-scale into hydrological concerns at the catchment scale.

Capabilities of stochastic rainfall models as data providers for urban hydrology

NASA Astrophysics Data System (ADS)

Haberlandt, Uwe

2017-04-01

For planning of urban drainage systems using hydrological models, long, continuous precipitation series with high temporal resolution are needed. Since observed time series are often too short or not available everywhere, the use of synthetic precipitation is a common alternative. This contribution compares three precipitation models regarding their suitability to provide 5 minute continuous rainfall time series for a) sizing of drainage networks for urban flood protection and b) dimensioning of combined sewage systems for pollution reduction. The rainfall models are a parametric stochastic model (Haberlandt et al., 2008), a non-parametric probabilistic approach (Bárdossy, 1998) and a stochastic downscaling of dynamically simulated rainfall (Berg et al., 2013); all models are operated both as single site and multi-site generators. The models are applied with regionalised parameters assuming that there is no station at the target location. Rainfall and discharge characteristics are utilised for evaluation of the model performance. The simulation results are compared against results obtained from reference rainfall stations not used for parameter estimation. The rainfall simulations are carried out for the federal states of Baden-Württemberg and Lower Saxony in Germany and the discharge simulations for the drainage networks of the cities of Hamburg, Brunswick and Freiburg. Altogether, the results show comparable simulation performance for the three models, good capabilities for single site simulations but low skills for multi-site simulations. Remarkably, there is no significant difference in simulation performance comparing the tasks flood protection with pollution reduction, so the models are finally able to simulate both the extremes and the long term characteristics of rainfall equally well. Bárdossy, A., 1998. Generating precipitation time series using simulated annealing. Wat. Resour. Res., 34(7): 1737-1744. Berg, P., Wagner, S., Kunstmann, H., Schädler, G., 2013. High resolution regional climate model simulations for Germany: part I — validation. Climate Dynamics, 40(1): 401-414. Haberlandt, U., Ebner von Eschenbach, A.-D., Buchwald, I., 2008. A space-time hybrid hourly rainfall model for derived flood frequency analysis. Hydrol. Earth Syst. Sci., 12: 1353-1367.

Performance of bias corrected MPEG rainfall estimate for rainfall-runoff simulation in the upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Worqlul, Abeyou W.; Ayana, Essayas K.; Maathuis, Ben H. P.; MacAlister, Charlotte; Philpot, William D.; Osorio Leyton, Javier M.; Steenhuis, Tammo S.

2018-01-01

In many developing countries and remote areas of important ecosystems, good quality precipitation data are neither available nor readily accessible. Satellite observations and processing algorithms are being extensively used to produce satellite rainfall products (SREs). Nevertheless, these products are prone to systematic errors and need extensive validation before to be usable for streamflow simulations. In this study, we investigated and corrected the bias of Multi-Sensor Precipitation Estimate-Geostationary (MPEG) data. The corrected MPEG dataset was used as input to a semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) for simulation of discharge of the Gilgel Abay and Gumara watersheds in the Upper Blue Nile basin, Ethiopia. The result indicated that the MPEG satellite rainfall captured 81% and 78% of the gauged rainfall variability with a consistent bias of underestimating the gauged rainfall by 60%. A linear bias correction applied significantly reduced the bias while maintaining the coefficient of correlation. The simulated flow using bias corrected MPEG SRE resulted in a simulated flow comparable to the gauge rainfall for both watersheds. The study indicated the potential of MPEG SRE in water budget studies after applying a linear bias correction.

Erosion measurements at various scales in a semi arid mountainous catchment - case of the Rheraya watershed, High Atlas, Morocco

NASA Astrophysics Data System (ADS)

Cheggour, A.; Simonneaux, V.; Roose, E.

2009-04-01

Erosion is a critical phenomenon in North Africa, under the combined effects of aggressive rainfall and soil fragility, increased by the grazing pressure on rangelands. However measurements of actual erosion rates are rare, especially in mountainous areas. Siltation of dams is estimated at more than 60 million m3 annually in Morocco, which corresponds to a decrease of 0.5% of the storage capacity. The Rheraya watershed (225 km2) is located in a semi-arid climat, in the High Atlas of Morocco. In order to assess erosion processes at various scales, three types of measurements were achieved on this area, namely rainfall simulation tests one square meter, erosion plots on 150 m2, and catchment's discharge and associated sediments measurements. Rainfall simulation experiments were achieved on 27 sites, measuring runoff and sediment charge. The turbidity was correctly measured thanks to the development of a new runoff collector which doesn't disturb the soil. In the scope of spatial extrapolation, we searched for indicators obtained from ground description variables and/or by laboratory tests on soil samples, which were well correlated with infiltration and turbidity of the simulations. For the various soils present in the study area, the results show a large variability of infiltration (from 1 to 70 mm h-1) and turbidity (from 3 to 325 g.l-1). Analysis showed that infiltration is correlated mainly with texture and soil surface opening, and that turbidity is related to the surface of bare soil exposed to runoff. Six erosion plots of about 150 m2, located on various soil and land cover conditions, were measured during four years. The observations showed very rare runoff events in the main part of the watershed, producing a low sediment load (between 0.015 and 2.5 t.ha1.year1). Conversely, runoff was much more frequent on silty badlands, producing about 95% of the watershed sediment (350 t.ha-1.year-1) despite their area was only 1% of the watershed. There was a significant linear relation between simulation turbidity and erosion plot turbidity. However, there was a great difference between infiltration estimates from the two types of measurements. Plot infiltrations estimates were only between 3 and 5 mm/h, but they were significantly correlated to the one from test, through an exponential relation. Finally, an estimate of the overall erosion at catchment's scale was achieved from plots values extrapolated using a soil map, and gave about 3 to 4 t.ha-1.year-1. A good correlation was found between this watershed scale estimate and the catchment's exportation, indirectly validating the significance of both measurements. Moreover, both estimates were about the same, showing a sediment delivery ratio around one. Keywords: erosion, rainfall simulation, erosion plot, sediment exportation

Qualitative comparison of soil erosion, runoff and infiltration coefficients using small portable rainfall simulators in Germany, Spain and France

NASA Astrophysics Data System (ADS)

Rodrigo Comino, Jesús; Iserloh, Thomas; Morvan, Xavier; Malam Issa, Oumarou; Naisse, Christophe; Keesstra, Saskia; Cerdà, Artemi; Prosdocimi, Massimo; Arnáez, José; Lasanta, Teodoro; Concepción Ramos, María; José Marqués, María; Ruiz Colmenero, Marta; Bienes, Ramón; Damián Ruiz Sinoga, José; Seeger, Manuel; Ries, Johannes B.

2016-04-01

Small portable rainfall simulators are considered as a useful tool to analyze soil erosion processes in cultivated lands. European research groups of Spain (Valencia, Málaga, Lleida, Madrid and La Rioja), France (Reims) or Germany (Trier) have used different rainfall simulators (varying in drop size distribution and fall velocities, kinetic energy, plot forms and sizes, and field of application)to study soil loss, surface flow, runoff and infiltration coefficients in different experimental plots (Valencia, Montes de Málaga, Penedès, Campo Real and La Rioja in Spain, Champagne in France and Mosel-Ruwer valley in Germany). The measurements and experiments developed by these research teams give an overview of the variety in the methodologies with rainfall simulations in studying the problem of soil erosion and describing the erosion features in different climatic environments, management practices and soil types. The aim of this study is: i) to investigate where, how and why researchers from different wine-growing regions applied rainfall simulations with successful results as a tool to measure soil erosion processes; ii) to make a qualitative comparison about the general soil erosion processes in European terroirs; iii) to demonstrate the importance of the development a standard method for soil erosion processes in vineyards, using rainfall simulators; iv) and to analyze the key factors that should be taken into account to carry out rainfall simulations. The rainfall simulations in all cases allowed knowing the infiltration capacity and the susceptibility of the soil to be detached and to generate sediment loads to runoff. Despite using small plots, the experiments were useful to analyze the influence of soil cover to reduce soil erosion and to make comparison between different locations or the influence of different soil characteristics.

An Experimental Study of Small-Scale Variability of Raindrop Size Distribution

NASA Technical Reports Server (NTRS)

Tokay, Ali; Bashor, Paul G.

2010-01-01

An experimental study of small-scale variability of raindrop size distributions (DSDs) has been carried out at Wallops Island, Virginia. Three Joss-Waldvogel disdrometers were operated at a distance of 0.65, 1.05, and 1.70 km in a nearly straight line. The main purpose of the study was to examine the variability of DSDs and its integral parameters of liquid water content, rainfall, and reflectivity within a 2-km array: a typical size of Cartesian radar pixel. The composite DSD of rain events showed very good agreement among the disdrometers except where there were noticeable differences in midsize and large drops in a few events. For consideration of partial beam filling where the radar pixel was not completely covered by rain, a single disdrometer reported just over 10% more rainy minutes than the rainy minutes when all three disdrometers reported rainfall. Similarly two out of three disdrometers reported5%more rainy minutes than when all three were reporting rainfall. These percentages were based on a 1-min average, and were less for longer averaging periods. Considering only the minutes when all three disdrometers were reporting rainfall, just over one quarter of the observations showed an increase in the difference in rainfall with distance. This finding was based on a 15-min average and was even less for shorter averaging periods. The probability and cumulative distributions of a gamma-fitted DSD and integral rain parameters between the three disdrometers had a very good agreement and no major variability. This was mainly due to the high percentage of light stratiform rain and to the number of storms that traveled along the track of the disdrometers. At a fixed time step, however, both DSDs and integral rain parameters showed substantial variability. The standard deviation (SD) of rain rate was near 3 mm/h, while the SD of reflectivity exceeded 3 dBZ at the longest separation distance. These standard deviations were at 6-min average and were higher at shorter averaging periods. The correlations decreased with increasing separation distance. For rain rate, the correlations were higher than previous gauge-based studies. This was attributed to the differences in data processing and the difference in rainfall characteristics in different climate regions. It was also considered that the gauge sampling errors could be a factor. In this regard, gauge measurements were simulated employing existing disdrometer dataset. While a difference was noticed in cumulative distribution of rain occurrence between the simulated gauge and disdrometer observations, the correlations in simulated gauge measurements did not differ from the disdrometer measurements.

Daily Rainfall Simulation Using Climate Variables and Nonhomogeneous Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jung, J.; Kim, H. S.; Joo, H. J.; Han, D.

2017-12-01

Markov chain is an easy method to handle when we compare it with other ones for the rainfall simulation. However, it also has limitations in reflecting seasonal variability of rainfall or change on rainfall patterns caused by climate change. This study applied a Nonhomogeneous Hidden Markov Model(NHMM) to consider these problems. The NHMM compared with a Hidden Markov Model(HMM) for the evaluation of a goodness of the model. First, we chose Gum river basin in Korea to apply the models and collected daily rainfall data from the stations. Also, the climate variables of geopotential height, temperature, zonal wind, and meridional wind date were collected from NCEP/NCAR reanalysis data to consider external factors affecting the rainfall event. We conducted a correlation analysis between rainfall and climate variables then developed a linear regression equation using the climate variables which have high correlation with rainfall. The monthly rainfall was obtained by the regression equation and it became input data of NHMM. Finally, the daily rainfall by NHMM was simulated and we evaluated the goodness of fit and prediction capability of NHMM by comparing with those of HMM. As a result of simulation by HMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.2076 and 10.8243/131.1304mm each. In case of NHMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.6652 and 10.5112/100.9865mm each. We could verify that the error of daily and monthly rainfall simulated by NHMM was improved by 2.89% and 22.99% compared with HMM. Therefore, it is expected that the results of the study could provide more accurate data for hydrologic analysis. Acknowledgements This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(2017R1A2B3005695)

The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

NASA Technical Reports Server (NTRS)

Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

2013-01-01

The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

Estimating the human influence on Hurricanes Harvey, Irma and Maria

NASA Astrophysics Data System (ADS)

Wehner, M. F.; Patricola, C. M.; Risser, M. D.

2017-12-01

Attribution of the human-induced climate change influence on the physical characteristics of individual extreme weather events has become an advanced science over the past decade. However, it is only recently that such quantification of anthropogenic influences on event magnitudes and probability of occurrence could be applied to very extreme storms such as hurricanes. We present results from two different classes of attribution studies for the impactful Atlantic hurricanes of 2017. The first is an analysis of the record rainfall amounts during Hurricane Harvey in the Houston, Texas area. We analyzed observed precipitation from the Global Historical Climatology Network with a covariate-based extreme value statistical analysis, accounting for both the external influence of global warming and the internal influence of ENSO. We found that human-induced climate change likely increased Hurricane Harvey's total rainfall by at least 19%, and likely increased the chances of the observed rainfall by a factor of at least 3.5. This suggests that changes exceeded Clausius-Clapeyron scaling, motivating attribution studies using dynamical climate models. The second analysis consists of two sets of hindcast simulations of Hurricanes Harvey, Irma, and Maria using the Weather Research and Forecasting model (WRF) at 4.5 km resolution. The first uses realistic boundary and initial conditions and present-day greenhouse gas forcings while the second uses perturbed conditions and pre-industrial greenhouse has forcings to simulate counterfactual storms without anthropogenic influences. These simulations quantify the fraction of Harvey's precipitation attributable to human activities and test the super Clausius-Clapeyron scaling suggested by the observational analysis. We will further quantify the human influence on intensity for Harvey, Irma, and Maria.

HYDROSCAPE: A SCAlable and ParallelizablE Rainfall Runoff Model for Hydrological Applications

NASA Astrophysics Data System (ADS)

Piccolroaz, S.; Di Lazzaro, M.; Zarlenga, A.; Majone, B.; Bellin, A.; Fiori, A.

2015-12-01

In this work we present HYDROSCAPE, an innovative streamflow routing method based on the travel time approach, and modeled through a fine-scale geomorphological description of hydrological flow paths. The model is designed aimed at being easily coupled with weather forecast or climate models providing the hydrological forcing, and at the same time preserving the geomorphological dispersion of the river network, which is kept unchanged independently on the grid size of rainfall input. This makes HYDROSCAPE particularly suitable for multi-scale applications, ranging from medium size catchments up to the continental scale, and to investigate the effects of extreme rainfall events that require an accurate description of basin response timing. Key feature of the model is its computational efficiency, which allows performing a large number of simulations for sensitivity/uncertainty analyses in a Monte Carlo framework. Further, the model is highly parsimonious, involving the calibration of only three parameters: one defining the residence time of hillslope response, one for channel velocity, and a multiplicative factor accounting for uncertainties in the identification of the potential maximum soil moisture retention in the SCS-CN method. HYDROSCAPE is designed with a simple and flexible modular structure, which makes it particularly prone to massive parallelization, customization according to the specific user needs and preferences (e.g., rainfall-runoff model), and continuous development and improvement. Finally, the possibility to specify the desired computational time step and evaluate streamflow at any location in the domain, makes HYDROSCAPE an attractive tool for many hydrological applications, and a valuable alternative to more complex and highly parametrized large scale hydrological models. Together with model development and features, we present an application to the Upper Tiber River basin (Italy), providing a practical example of model performance and characteristics.

Using molecular-scale tracers to investigate transport of agricultural pollutants in soil and water

NASA Astrophysics Data System (ADS)

Lloyd, C.; Michaelides, K.; Chadwick, D.; Dungait, J.; Evershed, R. P.

2012-12-01

We explore the use of molecular-scale tracers to investigate the transport of potential pollutants due to the application of slurry to soil. The molecular-scale approach allows us to separate the pollutants which are moved to water bodies through sediment-bound and dissolved transport pathways. Slurry is applied to agricultural land to as a soil-improver across a wide-range of topographic and climatic regimes, hence a set of experiments were designed to assess the effect of changing slope gradient and rainfall intensity on the transport of pollutants. The experiments were carried out using University of Bristol's TRACE (Test Rig for Advancing Connectivity Experiments) facility. The facility includes a dual axis soil slope (6 x 2.5 x 0.3 m3) and 6-nozzle rainfall simulator, which enables the manipulation of the slope to simulate different slope gradient and rainfall scenarios. Cattle slurry was applied to the top 1 metre strip of the experimental soil slope followed by four rainfall simulations, where the gradient (5° & 10°) and the rainfall intensity (60 & 120 mm hr-1) were co-varied. Leachate was sampled from different flow pathways (surface, subsurface and percolated) via multiple outlets on the slope throughout the experiments and soil cores were taken from the slope after each experiment. Novel tracers were used to trace the pollutants in both dissolved and sediment-bound forms. Fluorescence spectroscopy was used to trace dissolved slurry-derived material via water flow pathways, as the slurry was found to have a distinct signature compared with the soil. The fluorescence signatures of the leachates were compared with those of many organic compounds in order to characterise the origin of the signal. This allowed the assessment of the longevity of the signal in the environment to establish if it could be used as a robust long-term tracer of slurry material in water or if would be subject to transform processes through time. 5-βstanols, organic compounds unique to ruminant faeces, were used to trace the transport of sediment-bound pollutants from the slurry which could be transported into water bodies via erosion processes. The results showed that contributions of potential pollutants from the surface and subsurface flow pathways and from the eroded sediment differ according to slope gradient and rainfall intensity. Therefore, as the contribution of each of these pathways changes in response to rainfall and slope gradient, the pollution risk also changes accordingly, as different organic compounds are mobilised at varying rates. Rapid hydrological response to rainfall results in erosion and surface transport of sediment-bound and dissolved pollutants, creating an immediate contamination threat. However, conditions resulting in a slower hydrological response and the predominance of flow percolation over surface runoff results in higher rates of dissolved pollutant transport through the soil layers which risks contamination of subsurface and deeper ground-water systems. These experiments provide insight into the pathways and timing of contaminant transport with potential implications for understanding contamination risk from the transfer of slurry from land to water bodies. Understanding this threat is critical at a time when pressure is on to develop land-management strategies to reduce pollution alongside maintaining food security.

Modelling runoff and soil water content with the DR2-2013© SAGA v1.1 model at catchment scale under Mediterranean conditions (NE Spain)

NASA Astrophysics Data System (ADS)

López-Vicente, Manuel, , Dr.; Palazón, M. Sc. Leticia; Quijano, M. Sc. Laura; Gaspar, Leticia, , Dr.; Navas, Ana, , Dr.

2015-04-01

Hydrological and soil erosion models allow mapping and quantifying spatially distributed rates of runoff depth and soil redistribution for different land uses, management and tillage practices and climatic scenarios. The different temporal and spatial [very small (< 1 km2), small (1-5 km2), medium (5-50 km2) and large catchments (50-1000 km2) or river basins (>1000 km2)] scales of numerical simulations make model selection specific to each range of scales. Additionally, the spatial resolution of the inputs is in agreement with the size of the study area. In this study, we run the GIS-based water balance DR2-2013© SAGA v1.1 model (freely downloaded as executable file at http://digital.csic.es/handle/10261/93543), in the Vandunchil stream catchment (23 km2; Ebro river basin, NE Spain). All input maps are generated at 5 x 5 m of cell size (924,573 pixels per map) allowing sound parameterization. Simulation is run at monthly scale with average climatic values. This catchment is an open hydrological system and it has a long history of human occupation, agricultural practices and water management. Numerous manmade infrastructures or landscape linear elements (LLEs: paved and unpaved trails, rock mounds in non-cultivated areas, disperse and small settlements, shallow and long drainage ditches, stone walls, small rock dams, fences and vegetation strips) appear throughout the hillslopes and streams and modify the natural runoff pathways and thus the hydrological and sediment connectivity. Rain-fed cereal fields occupy one third of the catchment area, 1% corresponds to sealed soils, and the remaining area is covered with Mediterranean forest, scrubland, pine afforestation and meadow. The parent material corresponds to Miocene sandstones and lutites and Holocene colluvial and alluvial deposits. The climate is continental Mediterranean with two humid periods, one in spring and a second in autumn that summarizes 63% of the total annual precipitation. We created a synthetic weather station (WS) from the Caseda and Uncastillo WS. The effective rainfall that reaches the soils (after canopy interception and slope correction) was 85% on average from the total rainfall depth (556 mm yr-1) and the average initial runoff, before overland flow processes, was 320 mm yr-1. The simulated effective runoff (CQeff) ranged from 0 until 29,960 mm yr-1 and the corresponding map showed the typical spatial pattern of overland flow pathways though numerous disruptions appeared along the hillslopes and the main streams due to the presence of LLEs. The total depth of annual runoff corresponds to 37.8% of the total effective rainfall (TER) and 32.0% of the total rainfall depth (TR). The remaining volume of water, the soil water content (Waa) associated with the runoff and rainfall events, meant 62.2% and 52.7% of the TER and TR, respectively. The map of the Waa presented a different spatial pattern where the land uses play a more important role than the processes of cumulative overland flow. Significant variations in the monthly values of CQeff and Waa were described. This study proves the ability of the DR2-2013© SAGA v1.1 model to simulate the hydrological response of the soils at catchment scale.

Nonlinear effects of microtopography on macroscopic rainfall-runoff partitioning a the hillslope scale: a modelling study

NASA Astrophysics Data System (ADS)

Caviedes-Voullième, Daniel; Domin, Andrea; Hinz, Christoph

2017-04-01

The quantitative description and prediction of hydrological response of hillslopes or hillslope-scale catchments to rainfall events is becoming evermore relevant. At the hillslope scale, the onset of runoff and the overall rainfall-runoff transformation are controlled by multiple interacting small-scale processes, that, when acting together produce a response described in terms of hydrological variables well-defined at the catchment and hillslope scales. We hypothesize that small scale features such microtopography of the land surface will will govern large scale signatures of temporal runoff evolution. This can be tested directly by numerical modelling of well-defined surface geometries and adequate process description. It requires a modelling approach consistent with fundamental fluid mechanics, well-designed numerical methods, and computational efficiency. In this work, an idealized rectangular domain representing a hillslope with an idealized 2D sinusoidal microtopography is studied by simulating surface water redistribution by means of a 2D diffusive-wave (zero-inertia) shallow water model. By studying more than 500 surfaces and performing extensive sensitivity analysis forced by a single rainfall pulse, the dependency of characteristic hydrological responses to microtopographical properties was assessed. Despite of the simplicity of periodic surface and the rain event, results indicate complex surface flow dynamics during the onset of runoff observed at the macro and micro scales. Macro scale regimes were defined in terms of characteristics hydrograph shapes and those were related to surface geometry. The reference regime was defined for smooth topography and consisted of a simple hydrograph with smoothly rising and falling limbs with an intermediate steady state. In constrast, rough surface geometry yields stepwise rising limbs and shorter steady states. Furthermore, the increase in total infiltration over the whole domain relative to the smooth reference case shows a strong non-linear dependency on slope and the ratio of the characteristic wavelength and amplitude of microtopography. The coupled analysis of spatial and hydrological results also suggests that the hydrological behaviour can be explained by the spatiotemporal variations triggered by surface connectivity. This study significantly extents previous work on 1D domains, as our results reveal complexities that require 2D representation of the runoff processes.

An evaluation of the uncertainty of extreme events statistics at the WMO/CIMO Lead Centre on precipitation intensity

NASA Astrophysics Data System (ADS)

Colli, M.; Lanza, L. G.; La Barbera, P.

2012-12-01

Improving the quality of point-scale rainfall measurements is a crucial issue fostered in recent years by the WMO Commission for Instruments and Methods of Observation (CIMO) by providing recommendations on the standardization of equipment and exposure, instrument calibration and data correction as a consequence of various comparative campaigns involving manufacturers and national meteorological services from the participating countries. The WMO/CIMO Lead Centre on Precipitation Intensity (LC) was recently constituted, in a joint effort between the Dep. of Civil, Chemical and Environmental Engineering of the University of Genova and the Italian Air Force Met Service, gathering the considerable asset of data and information achieved by the past infield and laboratory campaigns with the aim of researching novel methodologies for improving the accuracy of rainfall intensity (RI) measurement techniques. Among the ongoing experimental activities carried out by the LC laboratory particular attention is paid to the reliability evaluation of extreme rainfall events statistics , a common tool in the engineering practice for urban and non urban drainage system design, based on real world observations obtained from weighing gauges. Extreme events statistics were proven already to be highly affected by the traditional tipping-bucket rain gauge RI measurement inaccuracy (La Barbera et al., 2002) and the time resolution of the available RI series certainly constitutes another key-factor in the reliability of the derived hyetographs. The present work reports the LC laboratory efforts in assembling a rainfall simulation system to reproduce the inner temporal structure of the rainfall process by means of dedicated calibration and validation tests. This allowed testing of catching type rain gauges under non-steady flow conditions and quantifying, in a first instance, the dynamic behaviour of the investigated instruments. Considerations about the influence of the dynamic response on the uncertainty budget of modern rain gauges is also shown . The analysis proceeds with the laboratory simulation of the annual maximum rainfall events recorded for different durations at the Villa Cambiaso meteo-station (University of Genova) over the last two decades. Results are reported and discussed in a comparative form involving the derived extreme events statistics. REFERENCES La Barbera P., Lanza L.G. and Stagi L. (2002). Influence of systematic mechanical errors of tipping-bucket rain gauges on the statistics of rainfall extremes. Water Sci. Techn., 45(2), 1-9. Colli M., Lanza L.G., and Chan P.W. (2011). Co-located tipping-bucket and optical drop counter RI measurements and a simulated correction algorithm, Atmos. Res., doi:10.1016/j.atmosres.2011.07.018 Colli M., Lanza L.G., La Barbera P. (2012). Weighing gauges measurement errors and the design rainfall for urban scale applications. 9th International workshop on precipitation in urban areas. St.Moritz, Switzerland, 6-9 December 2012 Lanza L.G. and Vuerich E. (2009). The WMO Field Intercomparison of Rain Intensity Gauges. Atmos. Res., 94, 534-543.

Multi-catchment rainfall-runoff simulation for extreme flood estimation

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel

2017-04-01

The SCHADEX method (Paquet et al., 2013) is a reference method in France for the estimation of extreme flood for dam design. The method is based on a semi-continuous rainfall-runoff simulation process: hundreds of different rainy events, randomly drawn up to extreme values, are simulated independently in the hydrological conditions of each day when a rainy event has been actually observed. This allows generating an exhaustive set of crossings between precipitation and soil saturation hazards, and to build a complete distribution of flood discharges up to extreme quantiles. The hydrological model used within SCHADEX, the MORDOR model (Garçon, 1996), is a lumped model, which implies that hydrological processes, e.g. rainfall and soil saturation, are supposed to be homogeneous throughout the catchment. Snow processes are nevertheless represented in relation with altitude. This hypothesis of homogeneity is questionable especially as the size of the catchment increases, or in areas of highly contrasted climatology (like mountainous areas). Conversely, modeling the catchment with a fully distributed approach would cause different problems, in particular distributing the rainfall-runoff model parameters trough space, and within the SCHADEX stochastic framework, generating extreme rain fields with credible spatio-temporal features. An intermediate solution is presented here. It provides a better representation of the hydro-climatic diversity of the studied catchment (especially regarding flood processes) while keeping the SCHADEX simulation framework. It consists in dividing the catchment in several, more homogeneous sub-catchments. Rainfall-runoff models are parameterized individually for each of them, using local discharge data if available. A first SCHADEX simulation is done at the global scale, which allows assigning a probability to each simulated event, mainly based on the global areal rainfall drawn for the event (see Paquet el al., 2013 for details). Then the rainfall of each event is distributed through the different sub-catchments using the spatial patterns calculated in the SPAZM precipitation reanalysis (Gottardi et al., 2012) for comparable situations of the 1948-2005 period. Corresponding runoffs are calculated with the hydrological models and aggregated to compute the discharge at the outlet of the main catchment. A complete distribution of flood discharges is finally computed. This method is illustrated with the example of the Durance at Serre-Ponçon catchment (south of French Alps, 3600 km2) which has been divided in four sub-catchements. The proposed approach is compared with the "classical" SCHADEX approach applied on the whole catchment. References: Garçon, R. (1996). Prévision opérationnelle des apports de la Durance à Serre-Ponçon à l'aide du modèle MORDOR. Bilan de l'année 1994-1995. La Houille Blanche, (5), 71-76. Gottardi, F., Obled, C., Gailhard, J., & Paquet, E. (2012). Statistical reanalysis of precipitation fields based on ground network data and weather patterns: Application over French mountains. Journal of Hydrology, 432, 154-167. Paquet, E., Garavaglia, F., Garçon, R., & Gailhard, J. (2013). The SCHADEX method: A semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 495, 23-37.

Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data.

PubMed

Flores-Alsina, Xavier; Saagi, Ramesh; Lindblom, Erik; Thirsing, Carsten; Thornberg, Dines; Gernaey, Krist V; Jeppsson, Ulf

2014-03-15

The objective of this paper is to demonstrate the full-scale feasibility of the phenomenological dynamic influent pollutant disturbance scenario generator (DIPDSG) that was originally used to create the influent data of the International Water Association (IWA) Benchmark Simulation Model No. 2 (BSM2). In this study, the influent characteristics of two large Scandinavian treatment facilities are studied for a period of two years. A step-wise procedure based on adjusting the most sensitive parameters at different time scales is followed to calibrate/validate the DIPDSG model blocks for: 1) flow rate; 2) pollutants (carbon, nitrogen); 3) temperature; and, 4) transport. Simulation results show that the model successfully describes daily/weekly and seasonal variations and the effect of rainfall and snow melting on the influent flow rate, pollutant concentrations and temperature profiles. Furthermore, additional phenomena such as size and accumulation/flush of particulates of/in the upstream catchment and sewer system are incorporated in the simulated time series. Finally, this study is complemented with: 1) the generation of additional future scenarios showing the effects of different rainfall patterns (climate change) or influent biodegradability (process uncertainty) on the generated time series; 2) a demonstration of how to reduce the cost/workload of measuring campaigns by filling the gaps due to missing data in the influent profiles; and, 3) a critical discussion of the presented results balancing model structure/calibration procedure complexity and prediction capabilities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Extreme rainfall-induced landslide changes based on landslide susceptibility in China, 1998-2015

NASA Astrophysics Data System (ADS)

Li, Weiyue; Liu, Chun; Hong, Yang

2017-04-01

Nowadays, landslide has been one of the most frequent and seriously widespread natural hazards all over the world. Rainfall, especially heavy rainfall is a trigger to cause the landslide occurrence, by increasing soil pore water pressures. In China, rainfall-induced landslides have risen up over to 90% of the total number. Rainfall events sometimes generate a trend of extremelization named rainfall extremes that induce the slope failure suddenly and severely. This study shows a method to simulate the rainfall-induced landslide spatio-temporal distribution on the basis of the landslide susceptibility index. First, the study on landslide susceptibility in China is introduced. We set the values of the index to the range between 0 and 1. Second, we collected TRMM 3B42 precipitation products spanning the years 1998-2015 and extracted the daily rainfall events greater than 50mm/day as extreme rainfall. Most of the rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours. The combination of these two aspects can be exploited to simulate extreme rainfall-induced landslide distribution and illustrate the changes in 17 years. This study shows a useful tool to be part of rainfall-induced landslide simulation methodology for landslide early warning.

Modeling the Large-scale Environments of Long-lived Mesoscale Convective Systems Conducive to Heavy Precipitation in the Central United States

NASA Astrophysics Data System (ADS)

Leung, L. R.; Houze, R.; Feng, Z.; Yang, Q.

2017-12-01

Mesoscale convective systems (MCSs) are important precipitation producers that account for 30-70% of warm season rainfall between the Rocky Mountains and Mississippi River and some 50-60% of tropical rainfall. Besides the tendency to produce floods, MCSs also carry with them a variety of attendant severe weather phenomena. Our recent analysis found that observed increases in springtime total and extreme rainfall in the central United States in the past 35 years are dominated by increased frequency and intensity of long-lasting MCSs. Understanding the environmental conditions producing long-lived MCSs is therefore a priority in determining how heavy precipitation events might change in character and location in a changing climate. Continental-scale convection-permitting simulations of the warm seasons using the WRF model reproduce realistic structure and frequency distribution of lifetime and event mean precipitation of MCSs over the central United States. The simulations show that MCSs systematically form over the central Great Plains ahead of a trough in the westerlies in combination with an enhanced low-level moist jet from the Gulf of Mexico. These environmental properties at the time of storm initiation are most prominent for the MCSs that persist for the longest times. MCSs reaching lifetimes of 9 h or more occur closer to the approaching trough than shorter-lived MCSs. These long-lived MCSs exhibit the strongest feedback to the environment through diabatic heating in the trailing regions of the MCSs that helps to maintain them over a long period of time. The identified large-scale and mesoscale ingredients provide a framework for understanding and modeling the potential changes in MCSs and associated hydrometeorological extremes in the future.

A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

NASA Astrophysics Data System (ADS)

Zhang, Shaojie; Zhao, Luqiang; Delgado-Tellez, Ricardo; Bao, Hongjun

2018-03-01

Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures

NASA Astrophysics Data System (ADS)

Kossieris, Panagiotis; Makropoulos, Christos; Onof, Christian; Koutsoyiannis, Demetris

2018-01-01

Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 min time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-min time scale. The applicability of the methodology was assessed on a 5-min rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

The Diurnal Cycle in TOGA-COARE: Regional Scale Model Simulations

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Jia, Y.

1999-01-01

The diurnal variation of precipitation processes over the tropics is a well-known phenomenon and has been studied using surface rainfall data, radar reflectivity data, and satellite-derived cloudiness and precipitation. Recently, analyzed observations from Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) in the tropical western Pacific ocean to study the relevant mechanisms producing diurnal variation of precipitation. They found that the diurnal Sea surface temperature (SST) cycle is important for afternoon showers in the undisturbed periods and diurnal radiative processes for nocturnal rainfall. Cloud resolving models (CRMS) have been used to determine the mechanisms associated with diurnal variation of precipitating processes. CRMs allow explicit cloud-radiation and air-sea interactive processes. However, CRMs can be only used for idealized simulations (i.e., no feedback between clouds and their embedded large-scale environments; cyclic lateral boundary conditions and idealized initial conditions). In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (covers the TOGA COARE LSA/IFA with a 54 km grid and can nest down to 18, 6 and possibly even 2 km) will be adopted for studying the diurnal variations of rainfall. We will examine precipitation processes over open ocean and over land. We will also perform sensitivity tests to determine how the radiative forcing and diurnal SST cycle affects the development of convection.

SWAT use of gridded observations for simulating runoff - a Vietnam river basin study

NASA Astrophysics Data System (ADS)

Vu, M. T.; Raghavan, S. V.; Liong, S. Y.

2011-12-01

Many research studies that focus on basin hydrology have used the SWAT model to simulate runoff. One common practice in calibrating the SWAT model is the application of station data rainfall to simulate runoff. But over regions lacking robust station data, there is a problem of applying the model to study the hydrological responses. For some countries and remote areas, the rainfall data availability might be a constraint due to many different reasons such as lacking of technology, war time and financial limitation that lead to difficulty in constructing the runoff data. To overcome such a limitation, this research study uses some of the available globally gridded high resolution precipitation datasets to simulate runoff. Five popular gridded observation precipitation datasets: (1) Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE), (2) Tropical Rainfall Measuring Mission (TRMM), (3) Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN), (4) Global Precipitation Climatology Project (GPCP), (5) modified Global Historical Climatology Network version 2 (GHCN2) and one reanalysis dataset National Centers for Environment Prediction/National Center for Atmospheric Research (NCEP/NCAR) are used to simulate runoff over the Dakbla River (a small tributary of the Mekong River) in Vietnam. Wherever possible, available station data are also used for comparison. Bilinear interpolation of these gridded datasets is used to input the precipitation data at the closest grid points to the station locations. Sensitivity Analysis and Auto-calibration are performed for the SWAT model. The Nash-Sutcliffe Efficiency (NSE) and Coefficient of Determination (R2) indices are used to benchmark the model performance. This entails a good understanding of the response of the hydrological model to different datasets and a quantification of the uncertainties in these datasets. Such a methodology is also useful for planning on Rainfall-runoff and even reservoir/river management both at rural and urban scales.

Rainfall simulation and Structure-from-Motion photogrammetry for the analysis of soil water erosion in Mediterranean vineyards.

PubMed

Prosdocimi, Massimo; Burguet, Maria; Di Prima, Simone; Sofia, Giulia; Terol, Enric; Rodrigo Comino, Jesús; Cerdà, Artemi; Tarolli, Paolo

2017-01-01

Soil water erosion is a serious problem, especially in agricultural lands. Among these, vineyards deserve attention, because they constitute for the Mediterranean areas a type of land use affected by high soil losses. A significant problem related to the study of soil water erosion in these areas consists in the lack of a standardized procedure of collecting data and reporting results, mainly due to a variability among the measurement methods applied. Given this issue and the seriousness of soil water erosion in Mediterranean vineyards, this works aims to quantify the soil losses caused by simulated rainstorms, and compare them with each other depending on two different methodologies: (i) rainfall simulation and (ii) surface elevation change-based, relying on high-resolution Digital Elevation Models (DEMs) derived from a photogrammetric technique (Structure-from-Motion or SfM). The experiments were carried out in a typical Mediterranean vineyard, located in eastern Spain, at very fine scales. SfM data were obtained from one reflex camera and a smartphone built-in camera. An index of sediment connectivity was also applied to evaluate the potential effect of connectivity within the plots. DEMs derived from the smartphone and the reflex camera were comparable with each other in terms of accuracy and capability of estimating soil loss. Furthermore, soil loss estimated with the surface elevation change-based method resulted to be of the same order of magnitude of that one obtained with rainfall simulation, as long as the sediment connectivity within the plot was considered. High-resolution topography derived from SfM revealed to be essential in the sediment connectivity analysis and, therefore, in the estimation of eroded materials, when comparing them to those derived from the rainfall simulation methodology. The fact that smartphones built-in cameras could produce as much satisfying results as those derived from reflex cameras is a high value added for using SfM. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic Rainfall Patterns and the Simulation of Changing Scenarios: A behavioral watershed response

NASA Astrophysics Data System (ADS)

Chu, M.; Guzman, J.; Steiner, J. L.; Hou, C.; Moriasi, D.

2015-12-01

Rainfall is one of the fundamental drivers that control hydrologic responses including runoff production and transport phenomena that consequently drive changes in aquatic ecosystems. Quantifying the hydrologic responses to changing scenarios (e.g., climate, land use, and management) using environmental models requires a realistic representation of probable rainfall in its most sensible spatio-temporal dimensions matching that of the phenomenon under investigation. Downscaling projected rainfall from global circulation models (GCMs) is the most common practice in deriving rainfall datasets to be used as main inputs to hydrologic models which in turn are used to assess the impacts of climate changes on ecosystems. Downscaling assumes that local climate is a combination of large-scale climatic/atmospheric conditions and local conditions. However, the representation of the latter is generally beyond the capacity of current GCMs. The main objective of this study was to develop and implement a synthetic rainfall generator to downscale expected rainfall trends to 1 x 1 km rainfall daily patterns that mimic the dynamic propagation of probability distribution functions (pdf) derived from historic rainfall data (rain-gauge or radar estimated). Future projections were determined based on actual and expected changes in the pdf and stochastic processes to account for variability. Watershed responses in terms of streamflow and nutrients loads were evaluated using synthetically generated rainfall patterns and actual data. The framework developed in this study will allow practitioners to generate rainfall datasets that mimic the temporal and spatial patterns exclusive to their study area under full disclosure of the uncertainties involved. This is expected to provide significantly more accurate environmental models than is currently available and would provide practitioners with ways to evaluate the spectrum of systemic responses to changing scenarios.

Use of dynamical downscaling to improve the simulation of Central U.S. warm season precipitation in CMIP5 models

NASA Astrophysics Data System (ADS)

Harding, Keith J.; Snyder, Peter K.; Liess, Stefan

2013-11-01

supporting exceptionally productive agricultural lands, the Central U.S. is susceptible to severe droughts and floods. Such precipitation extremes are expected to worsen with climate change. However, future projections are highly uncertain as global climate models (GCMs) generally fail to resolve precipitation extremes. In this study, we assess how well models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate summer means, variability, extremes, and the diurnal cycle of Central U.S. summer rainfall. Output from a subset of historical CMIP5 simulations are used to drive the Weather Research and Forecasting model to determine whether dynamical downscaling improves the representation of Central U.S. rainfall. We investigate which boundary conditions influence dynamically downscaled precipitation estimates and identify GCMs that can reasonably simulate precipitation when downscaled. The CMIP5 models simulate the seasonal mean and variability of summer rainfall reasonably well but fail to resolve extremes, the diurnal cycle, and the dynamic forcing of precipitation. Downscaling to 30 km improves these characteristics of precipitation, with the greatest improvement in the representation of extremes. Additionally, sizeable diurnal cycle improvements occur with higher (10 km) resolution and convective parameterization disabled, as the daily rainfall peak shifts 4 h closer to observations than 30 km resolution simulations. This lends greater confidence that the mechanisms responsible for producing rainfall are better simulated. Because dynamical downscaling can more accurately simulate these aspects of Central U.S. summer rainfall, policymakers can have added confidence in dynamically downscaled rainfall projections, allowing for more targeted adaptation and mitigation.

Improvement of Systematic Bias of mean state and the intraseasonal variability of CFSv2 through superparameterization and revised cloud-convection-radiation parameterization

NASA Astrophysics Data System (ADS)

Mukhopadhyay, P.; Phani Murali Krishna, R.; Goswami, Bidyut B.; Abhik, S.; Ganai, Malay; Mahakur, M.; Khairoutdinov, Marat; Dudhia, Jimmy

2016-05-01

Inspite of significant improvement in numerical model physics, resolution and numerics, the general circulation models (GCMs) find it difficult to simulate realistic seasonal and intraseasonal variabilities over global tropics and particularly over Indian summer monsoon (ISM) region. The bias is mainly attributed to the improper representation of physical processes. Among all the processes, the cloud and convective processes appear to play a major role in modulating model bias. In recent times, NCEP CFSv2 model is being adopted under Monsoon Mission for dynamical monsoon forecast over Indian region. The analyses of climate free run of CFSv2 in two resolutions namely at T126 and T382, show largely similar bias in simulating seasonal rainfall, in capturing the intraseasonal variability at different scales over the global tropics and also in capturing tropical waves. Thus, the biases of CFSv2 indicate a deficiency in model's parameterization of cloud and convective processes. Keeping this in background and also for the need to improve the model fidelity, two approaches have been adopted. Firstly, in the superparameterization, 32 cloud resolving models each with a horizontal resolution of 4 km are embedded in each GCM (CFSv2) grid and the conventional sub-grid scale convective parameterization is deactivated. This is done to demonstrate the role of resolving cloud processes which otherwise remain unresolved. The superparameterized CFSv2 (SP-CFS) is developed on a coarser version T62. The model is integrated for six and half years in climate free run mode being initialised from 16 May 2008. The analyses reveal that SP-CFS simulates a significantly improved mean state as compared to default CFS. The systematic bias of lesser rainfall over Indian land mass, colder troposphere has substantially been improved. Most importantly the convectively coupled equatorial waves and the eastward propagating MJO has been found to be simulated with more fidelity in SP-CFS. The reason of such betterment in model mean state has been found to be due to the systematic improvement in moisture field, temperature profile and moist instability. The model also has better simulated the cloud and rainfall relation. This initiative demonstrates the role of cloud processes on the mean state of coupled GCM. As the superparameterization approach is computationally expensive, so in another approach, the conventional Simplified Arakawa Schubert (SAS) scheme is replaced by a revised SAS scheme (RSAS) and also the old and simplified cloud scheme of Zhao-Karr (1997) has been replaced by WSM6 in CFSV2 (hereafter CFS-CR). The primary objective of such modifications is to improve the distribution of convective rain in the model by using RSAS and the grid-scale or the large scale nonconvective rain by WSM6. The WSM6 computes the tendency of six class (water vapour, cloud water, ice, snow, graupel, rain water) hydrometeors at each of the model grid and contributes in the low, middle and high cloud fraction. By incorporating WSM6, for the first time in a global climate model, we are able to show a reasonable simulation of cloud ice and cloud liquid water distribution vertically and spatially as compared to Cloudsat observations. The CFS-CR has also showed improvement in simulating annual rainfall cycle and intraseasonal variability over the ISM region. These improvements in CFS-CR are likely to be associated with improvement of the convective and stratiform rainfall distribution in the model. These initiatives clearly address a long standing issue of resolving the cloud processes in climate model and demonstrate that the improved cloud and convective process paramterizations can eventually reduce the systematic bias and improve the model fidelity.

Lower Boundary Forcing related to the Occurrence of Rain in the Tropical Western Pacific

NASA Astrophysics Data System (ADS)

Li, Y.; Carbone, R. E.

2013-12-01

Global weather and climate models have a long and somewhat tortured history with respect to simulation and prediction of tropical rainfall in the relative absence of balanced flow in the geostrophic sense. An important correlate with tropical rainfall is sea surface temperature (SST). The introduction of SST information to convective rainfall parameterization in global models has improved model climatologies of tropical oceanic rainfall. Nevertheless, large systematic errors have persisted, several of which are common to most atmospheric models. Models have evolved to the point where increased spatial resolution demands representation of the SST field at compatible temporal and spatial scales, leading to common usage of monthly SST fields at scales of 10-100 km. While large systematic errors persist, significant skill has been realized from various atmospheric and coupled ocean models, including assimilation of weekly or even daily SST fields, as tested by the European Center for Medium Range Weather Forecasting. A few investigators have explored the role of SST gradients in relation to the occurrence of precipitation. Some of this research has focused on large scale gradients, mainly associated with surface ocean-atmosphere climatology. These studies conclude that lower boundary atmospheric convergence, under some conditions, could be substantially enhanced over SST gradients, destabilizing the atmosphere, and thereby enabling moist convection. While the concept has a firm theoretical foundation, it has not gained a sizeable following far beyond the realm of western boundary currents. Li and Carbone 2012 examined the role of transient mesoscale (~ 100 km) SST gradients in the western Pacific warm pool by means of GHRSST and CMORPH rainfall data. They found that excitation of deep moist convection was strongly associated with the Laplacian of SST (LSST). Specifically, -LSST is associated with rainfall onset in 75% of 10,000 events over 4 years, whereas the background ocean is symmetric about zero Laplacian. This finding is fully consistent with theory for gradients of order ~1degC in low mean wind conditions, capable of inducing atmospheric convergence of N x 10-5s-1. We will present new findings resulting from the application of a Madden-Julian oscillation (MJO) passband filter to GHRSST/CMORPH data. It shows that the -LSST field organizes at scales of 1000-2000 km and can persist for periods of two weeks to 3 months. Such -LSST anomalies are in quadrature with MJO rainfall, tracking and leading the wet phase of the MJO by 10-14 days, from the Indian Ocean to the dateline. More generally, an evaluation of SST structure in rainfall production will be presented, which represents a decidedly alternative view to conventional wisdom. Li, Yanping, and R.E. Carbone, 2012: Excitation of Rainfall over the Tropical Western Pacific, J. Atmos. Sci., 69, 2983-2994.

A laboratory rainfall simulator to study the soil erosion and runoff water

NASA Astrophysics Data System (ADS)

Cancelo González, Javier; Rial, M. E.; Díaz-Fierros, Francisco

2010-05-01

The soil erosion and the runoff water composition in some areas affected by forest fires or submitted to intensive agriculture are an important factor to keep an account, particularly in sensitive areas like estuary and rias that have a high importance in the socioeconomic development of some regions. An understanding of runoff production indicates the processes by which pollutants reach streams and also indicates the management techniques that might be uses to minimize the discharge of these materials into surface waters. One of the most methodology implemented in the soil erosion studies is a rainfall simulation. This method can reproduce the natural soil degradation processes in field or laboratory experiences. With the aim of improve the rainfall-runoff generation, a laboratory rainfall simulator which incorporates a fan-like intermittent water jet system for rainfall generation were modified. The major change made to the rainfall simulator consist in a system to coupling stainless steel boxes, whose dimensions are 12 x 20 x 45 centimeters, and it allows to place soil samples under the rainfall simulator. Previously these boxes were used to take soil samples in field with more of 20 centimeters of depth, causing the minimum disturbance in their properties and structure. These new implementations in the rainfall simulator also allow collect water samples of runoff in two ways: firstly, the rain water that constituted the overland flow or direct runoff and besides the rain water seeps into the soil by the process of infiltration and contributed to the subsurface runoff. Among main the variables controlled in the rainfall simulations were the soil slope and the intensity and duration of rainfall. With the aim of test the prototype, six soil samples were collected in the same sampling point and subjected to rainfall simulations in laboratory with the same intensity and duration. Two samples will constitute the control test, and they were fully undisturbed, and four samples were subjected to controlled burnings with different fire severity: two samples burnt to 250°C and the other two samples burnt to 450°C. Preliminary laboratory data of soil erosion and surface and subsurface runoff were obtained. The water parameters analysed were: pH, electrical conductivity, temperature (in the moment of sampling) and suspended sediments, ammonium, nitrates, total nitrogen (Kjeldahl method), within 24 hours after sampling.

Soil erosion under multiple time-varying rainfall events

NASA Astrophysics Data System (ADS)

Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.

2010-05-01

Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.

A software-based sensor for combined sewer overflows.

PubMed

Leonhardt, G; Fach, S; Engelhard, C; Kinzel, H; Rauch, W

2012-01-01

A new methodology for online estimation of excess flow from combined sewer overflow (CSO) structures based on simulation models is presented. If sufficient flow and water level data from the sewer system is available, no rainfall data are needed to run the model. An inverse rainfall-runoff model was developed to simulate net rainfall based on flow and water level data. Excess flow at all CSO structures in a catchment can then be simulated with a rainfall-runoff model. The method is applied to a case study and results show that the inverse rainfall-runoff model can be used instead of missing rain gauges. Online operation is ensured by software providing an interface to the SCADA-system of the operator and controlling the model. A water quality model could be included to simulate also pollutant concentrations in the excess flow.

Relating rainfall characteristics to cloud top temperatures at different scales

NASA Astrophysics Data System (ADS)

Klein, Cornelia; Belušić, Danijel; Taylor, Christopher

2017-04-01

Extreme rainfall from mesoscale convective systems (MCS) poses a threat to lives and livelihoods of the West African population through increasingly frequent devastating flooding and loss of crops. However, despite the significant impact of such extreme events, the dominant processes favouring their occurrence are still under debate. In the data-sparse West African region, rainfall radar data from the Tropical Rainfall Measuring Mission (TRMM) gives invaluable information on the distribution and frequency of extreme rainfall. The TRMM 2A25 product provides a 15-year dataset of snapshots of surface rainfall from 2-4 overpasses per day. Whilst this sampling captures the overall rainfall characteristics, it is neither long nor frequent enough to diagnose changes in MCS properties, which may be linked to the trend towards rainfall intensification in the region. On the other hand, Meteosat geostationary satellites provide long-term sub-hourly records of cloud top temperatures, raising the possibility of combining these with the high-quality rainfall data from TRMM. In this study, we relate TRMM 2A25 rainfall to Meteosat Second Generation (MSG) cloud top temperatures, which are available from 2004 at 15 minutes intervals, to get a more detailed picture of the structure of intense rainfall within the life cycle of MCS. We find TRMM rainfall intensities within an MCS to be strongly coupled with MSG cloud top temperatures: the probability for extreme rainfall increases from <10% for minimum temperatures warmer than -40°C to over 70% when temperatures drop below -70°C, confirming the potential in analysing cloud-top temperatures as a proxy for extreme rain. The sheer size of MCS raises the question which scales of sub-cloud structures are more likely to be associated with extreme rain than others. In the end, this information could help to associate scale changes in cloud top temperatures with processes that affect the probability of extreme rain. We use 2D continuous wavelets to decompose cloud top temperatures into power spectra at scales between 15 and 200km. From these, cloud sub-structures are identified as circular areas of respective scale with local power maxima in their centre. These areas are then mapped onto coinciding TRMM rainfall, allowing us to assign rainfall fields to sub-cloud features of different scales. We find a higher probability for extreme rainfall for cloud features above a scale of 30km, with features 100km contributing most to the number of extreme rainfall pixels. Over the average diurnal cycle, the number of smaller cloud features between 15-60km shows an increase between 15 - 1700UTC, gradually developing into larger ones. The maximum of extreme rainfall pixels around 1900UTC coincides with a peak for scales 100km, suggesting a dominant role of these scales for intense rain for the analysed cloud type. Our results demonstrate the suitability of 2D wavelet decomposition for the analysis of sub-cloud structures and their relation to rainfall characteristics, and help us to understand long-term changes in the properties of MCS.

Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

NASA Astrophysics Data System (ADS)

Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

2017-12-01

This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

The hydrological behaviour of extensive and intensive green roofs in a dry climate.

PubMed

Razzaghmanesh, M; Beecham, S

2014-11-15

This paper presents the results of a hydrological investigation of four medium scale green roofs that were set up at the University of South Australia. In this study, the potential of green roofs as a source control device was investigated over a 2 year period using four medium size green roof beds comprised of two growth media types and two media depths. During the term of this study, 226 rainfall events were recorded and these were representative of the Adelaide climate. In general, there were no statistically significant differences between the rainfall and runoff parameters for the intensive and extensive beds except for peak attenuation and peak runoff delay, for which higher values were recorded in the intensive beds. Longer dry periods generally resulted in higher retention coefficients and higher retention was also recorded in warmer seasons. The average retention coefficient for intensive systems (89%) was higher than for extensive systems (74%). It was shown that rainfall depth, intensity, duration and also average dry weather period between events can change the retention performance and runoff volume of the green roofs. Comparison of green and simulated conventional roofs indicated that the former were able to mitigate the peak of runoff and could delay the start of runoff. These characteristics are important for most source control measures. The recorded rainfall and runoff data displayed a non-linear relationship. Also, the results indicated that continuous time series modelling would be a more appropriate technique than using peak rainfall intensity methods for green roof design and simulation. Copyright © 2014 Elsevier B.V. All rights reserved.

Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2007-12-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

Extreme Rainfall from Hurricane Harvey (2017): Intercomparisons of WRF Simulations and Polarimetric Radar Fields

NASA Astrophysics Data System (ADS)

Yang, L.; Smith, J. A.; Liu, M.; Baeck, M. L.; Chaney, M. M.; Su, Y.

2017-12-01

Hurricane Harvey made landfall on 25 August 2017 and produced more than a meter of rain during a four-day period over eastern Texas, making it the wettest tropical cyclone on record in the United States. Extreme rainfall from Harvey was predominantly related to the dynamics and structure of outer rain bands. In this study, we provide details of the extreme rainfall produced by Hurricane Harvey. The principal research questions that motivate this study are: (1) what are the key microphysical properties of extreme rainfall from landfalling tropical cyclones and (2) what are the capabilities and deficiencies of existing bulk microphysics parameterizations from the physical models in capturing them. Our analyses are centered on intercomparisons of high-resolution simulations using the Weather Research and Forecasting (WRF) model and polarimetric radar fields from KHGX (Houston, Texas) WSR-88D. The WRF simulations accurately capture the track and intensity of Hurricane Harvey. Multi-rainband structure and its key evolution features are also well represented in the simulations. Two microphysics parameterizations (WSM6 and WDM6) are tested in this study. Radar reflectivity and differential reflectivity fields simulated by the WRF model are compared with polarimetric radar observations. An important feature for the extreme rainfall from Hurricane Harvey is the sharp boundary of spatial rainfall accumulation along the coast (with torrential rainfall distributed over Houston and its surrounding inland areas). We will examine the role of land-sea contrasts in dictating storm structure and evolution from both WRF simulations and polarimetric radar fields. Implications for improving hurricane rainfall forecasts and estimates will be provided.

Using small-scale rainfall simulation to assess temporal changes in pre- and post-fire soil hydrology and erosion: the value of fixed-position plots

NASA Astrophysics Data System (ADS)

Ferreira, Carla S. S.; Shakesby, Rick A.; Bento, Célia P. M.; Walsh, Rory P. D.; Ferreira, António J. D.

2013-04-01

In recent decades, wildfire has become both frequent and severe in southern Europe leading to widespread research into its impacts on soil erosion, soil and water quality. Rainfall simulation has become established as a popular technique to assess these impacts, as it can be conducted under controlled conditions (notably, with respect to rainfall) and is a very cost-effective and rapid way to compare overland flow and suspended sediment generation within burned and unburned sites. Particular advantages are that: (1) results can be obtained before the first post-fire rainfall events; and (2) experiments can reproduce controlled storm events, with similar characteristics to natural rain. Although plot sizes vary (0.09-30m2), most researchers have used < 1m2 plots because of logistical difficulties of setting up larger plots especially in burned areas that may lack good access and local water supplies. Disadvantages with using small plots, however, particularly on burned terrain, include: (1) the difficulty of installing the plots without disturbing the soil; (2) the strong influence of plot boundaries on overland flow and sediment production. Significant replication is generally considered necessary to take account of high variability in results that are due in part to these effects. One response to these problems is a 'fixed plot' approach in which bounded plots are left in place for re-use throughout the study. A problem here, however, would be progressive sediment exhaustion due to the 'island' effect of the plots caused by their isolation from upslope sediment transfer. This paper assesses the usefulness of a repeat-simulation plot approach in assessing temporal change in overland flow and erosion in post-fire situations that minimizes the island effect by partial removal of plot boundaries between surveys. This approach was tested over a 2.5-year period in a small (9 ha) catchment in central Portugal subjected to an experimental fire in 2009. Five rainfall simulation plots 0.25m2 in size were installed close to sediment traps (contributing areas: 498-4238m2) collecting sediment eroded by overland flow caused by natural rainfall. The plots were installed pre-fire and experiments carried out under 'dry' and 'wet' antecedent conditions on six occasions from pre-fire to two years after the fire. The lateral boundaries of each plot were left in place, but the upslope boundary and central (outlet) section of the downslope boundary were removed between surveys and re-installed and sealed each time measurements were carried out. Having fixed positions of plots minimised soil disturbance on each monitoring occasion and meant that, for any given plot, results were directly comparable and gave a more reliable picture of change through time. Removing the upper and lower boundaries of the plots between measurements allowed the soil to undergo processes similar to those on the surrounding slope and reduced the 'island' effect associated with continuously bounded plots. Results from the adjacent sediment traps, which provided a parallel temporal record of hillslope-scale overland flow and sediment redistribution patterns under natural rainfall, are used to judge the usefulness of the in situ simulation plots approach.

A small single-nozzle rainfall simulator to measure erosion response on different burn severities in southern British Columbia, Canada

NASA Astrophysics Data System (ADS)

Covert, Ashley; Jordan, Peter

2010-05-01

To study the effects of wildfire burn severity on runoff generation and soil erosion from high intensity rainfall, we constructed an effective yet simple rainfall simulator that was inexpensive, portable and easily operated by two people on steep, forested slopes in southern British Columbia, Canada. The entire apparatus, including simulator, pumps, hoses, collapsible water bladders and sample bottles, was designed to fit into a single full-sized pick-up truck. The three-legged simulator extended to approximately 3.3 metres above ground on steep slopes and used a single Spraying Systems 1/2HH-30WSQ nozzle which can easily be interchanged for other sized nozzles. Rainfall characteristics were measured using a digital camera which took images of the raindrops against a grid. Median drop size and velocity 5 cm above ground were measured and found to be 3/4 of the size of natural rain drops of that diameter class, and fell 7% faster than terminal velocity. The simulator was used for experiments on runoff and erosion on sites burned in 2007 by two wildfires in southern British Columbia. Simulations were repeated one and two years after the fires. Rainfall was simulated at an average rate of 67 mm hr-1 over a 1 m2 plot for 20 minutes. This rainfall rate is similar to the 100 year return period rainfall intensity for this duration at a nearby weather station. Simulations were conducted on five replicate 1 m2 plots in each experimental unit including high burn severity, moderate burn severity, unburned, and unburned with forest floor removed. During the simulation a sample was collected for 30 seconds every minute, with two additional samples until runoff ceased, resulting in 22 samples per simulation. Runoff, overland flow coefficient, infiltration and sediment yield were compared between treatments. Additional simulations were conducted immediately after a 2009 wildfire to test different mulch treatments. Typical results showed that runoff on plots with high burn severity and with forest floor removed was similar, reaching on average a steady rate of about 60% of rainfall rate after about 7 minutes. Runoff on unburned plots with intact forest floor was much lower, typically less than 20% of rainfall rate. Sediment yield was greatest on plots with forest floor removed, followed by severely burned plots. Sediment yield on unburned and moderately burned plots was very low to zero. These results are consistent with qualitative observations made following several extreme rainfall events on recent burns in the region.

Hydrograph simulation models of the Hillsborough and Alafia Rivers, Florida: a preliminary report

USGS Publications Warehouse

Turner, James F.

1972-01-01

Mathematical (digital) models that simulate flood hydrographs from rainfall records have been developed for the following gaging stations in the Hillsborough and Alafia River basins of west-central Florida: Hillsborough River near Tampa, Alafia River at Lithia, and north Prong Alafia River near Keysville. These models, which were developed from historical streamflow and and rainfall records, are based on rainfall-runoff and unit-hydrograph procedures involving an arbitrary separation of the flood hydrograph. These models assume the flood hydrograph to be composed of only two flow components, direct (storm) runoff, and base flow. Expressions describing these two flow components are derived from streamflow and rainfall records and are combined analytically to form algorithms (models), which are programmed for processing on a digital computing system. Most Hillsborough and Alafia River flood discharges can be simulated with expected relative errors less than or equal to 30 percent and flood peaks can be simulated with average relative errors less than 15 percent. Because of the inadequate rainfall network that is used in obtaining input data for the North Prong Alafia River model, simulated peaks are frequently in error by more than 40 percent, particularly for storms having highly variable areal rainfall distribution. Simulation errors are the result of rainfall sample errors and, to a lesser extent, model inadequacy. Data errors associated with the determination of mean basin precipitation are the result of the small number and poor areal distribution of rainfall stations available for use in the study. Model inadequacy, however, is attributed to the basic underlying theory, particularly the rainfall-runoff relation. These models broaden and enhance existing water-management capabilities within these basins by allowing the establishment and implementation of programs providing for continued development in these areas. Specifically, the models serve not only as a basis for forecasting floods, but also for simulating hydrologic information needed in flood-plain mapping and delineating and evaluating alternative flood control and abatement plans.

The rainfall plot: its motivation, characteristics and pitfalls.

PubMed

Domanska, Diana; Vodák, Daniel; Lund-Andersen, Christin; Salvatore, Stefania; Hovig, Eivind; Sandve, Geir Kjetil

2017-05-18

A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

A Physically-based Model For Rainfall-triggered Landslides At A Regional Scale

NASA Astrophysics Data System (ADS)

Teles, V.; Capolongo, D.; Bras, R. L.

Rainfall has long been recognized as a major cause of landslides. Historical records have shown that large rainfall can generate hundreds of landslides over hundreds of square kilometers. Although a great body of work has documented the morphology and mechanics of individual slope failure, few studies have considered the process at basin and regional scale. A landslide model is integrated in the landscape evolution model CHILD and simulates rainfall-triggered events based on a geotechnical index, the factor of safety, which takes into account the slope, the soil effective cohesion and weight, the friction angle, the regolith thickness and the saturated thickness. The stat- urated thickness is represented by the wetness index developed in the TOPMODEL. The topography is represented by a Triangulated Irregular Network (TIN). The factor of safety is computed at each node of the TIN. If the factor of safety is lower than 1, a landslide is intiated at this node. The regolith is then moved downstream. We applied the model to the Fortore basin whose valley cuts the flysch terrain that constitute the framework of the so called "sub-Apennines" chain that is the most eastern part of the Southern Apennines (Italy). We will discuss its value according to its sensitivity to the used parameters and compare it to the actual data available for this basin.

Evaluation of empirical relationships between extreme rainfall and daily maximum temperature in Australia

NASA Astrophysics Data System (ADS)

Herath, Sujeewa Malwila; Sarukkalige, Ranjan; Nguyen, Van Thanh Van

2018-01-01

Understanding the relationships between extreme daily and sub-daily rainfall events and their governing factors is important in order to analyse the properties of extreme rainfall events in a changing climate. Atmospheric temperature is one of the dominant climate variables which has a strong relationship with extreme rainfall events. In this study, a temperature-rainfall binning technique is used to evaluate the dependency of extreme rainfall on daily maximum temperature. The Clausius-Clapeyron (C-C) relation was found to describe the relationship between daily maximum temperature and a range of rainfall durations from 6 min up to 24 h for seven Australian weather stations, the stations being located in Adelaide, Brisbane, Canberra, Darwin, Melbourne, Perth and Sydney. The analysis shows that the rainfall - temperature scaling varies with location, temperature and rainfall duration. The Darwin Airport station shows a negative scaling relationship, while the other six stations show a positive relationship. To identify the trend in scaling relationship over time the same analysis is conducted using data covering 10 year periods. Results indicate that the dependency of extreme rainfall on temperature also varies with the analysis period. Further, this dependency shows an increasing trend for more extreme short duration rainfall and a decreasing trend for average long duration rainfall events at most stations. Seasonal variations of the scale changing trends were analysed by categorizing the summer and autumn seasons in one group and the winter and spring seasons in another group. Most of 99th percentile of 6 min, 1 h and 24 h rain durations at Perth, Melbourne and Sydney stations show increasing trend for both groups while Adelaide and Darwin show decreasing trend. Furthermore, majority of scaling trend of 50th percentile are decreasing for both groups.

Assessment on spatiotemporal relationship between rainfall and cloud top temperature from new generation weather satellite imagery

NASA Astrophysics Data System (ADS)

Wei, Chiang; Yeh, Hui-Chung; Chen, Yen-Chang

2017-04-01

This study addressed the relationship between rainfall and cloud top temperature (CCT) from new generation satellite Himawari-8 imagery at different spatiotemporal scale. This satellite provides higher band, more bits for data format, spatial and temporal resolution compared with previous GMS series. The multi-infrared channels with 10-minute and 1-2 km resolution make it possible for rainfall estimating/forecasting in small/medium watershed. The preliminary result investigated at Chenyulan watershed (443.6 square kilometer) of Central Taiwan in 2016 Typhoon Megi shows the regression coefficient fitted by negative exponential equation of largest rainfall vs. CCT (B8 band) at pixel scale increases as time scales enlarges and reach 0.462 for 120-minute accumulative rainfall; the value (CTT of B15 band) decreases from 0.635 for 10-minute to 0.423 for 120-minute accumulative rainfall at basin-wide scale. More rainfall events for different regime are yet to evaluate to get solid results.

Calibration of three rainfall simulators with automatic measurement methods

NASA Astrophysics Data System (ADS)

Roldan, Margarita

2010-05-01

CALIBRATION OF THREE RAINFALL SIMULATORS WITH AUTOMATIC MEASUREMENT METHODS M. Roldán (1), I. Martín (2), F. Martín (2), S. de Alba(3), M. Alcázar(3), F.I. Cermeño(3) 1 Grupo de Investigación Ecología y Gestión Forestal Sostenible. ECOGESFOR-Universidad Politécnica de Madrid. E.U.I.T. Forestal. Avda. Ramiro de Maeztu s/n. Ciudad Universitaria. 28040 Madrid. margarita.roldan@upm.es 2 E.U.I.T. Forestal. Avda. Ramiro de Maeztu s/n. Ciudad Universitaria. 28040 Madrid. 3 Facultad de Ciencias Geológicas. Universidad Complutense de Madrid. Ciudad Universitaria s/n. 28040 Madrid The rainfall erosivity is the potential ability of rain to cause erosion. It is function of the physical characteristics of rainfall (Hudson, 1971). Most expressions describing erosivity are related to kinetic energy or momentum and so with drop mass or size and fall velocity. Therefore, research on factors determining erosivity leds to the necessity to study the relation between fall height and fall velocity for different drop sizes, generated in a rainfall simulator (Epema G.F.and Riezebos H.Th, 1983) Rainfall simulators are one of the most used tools for erosion studies and are used to determine fall velocity and drop size. Rainfall simulators allow repeated and multiple measurements The main reason for use of rainfall simulation as a research tool is to reproduce in a controlled way the behaviour expected in the natural environment. But in many occasions when simulated rain is used in order to compare it with natural rain, there is a lack of correspondence between natural and simulated rain and this can introduce some doubt about validity of data because the characteristics of natural rain are not adequately represented in rainfall simulation research (Dunkerley D., 2008). Many times the rainfall simulations have high rain rates and they do not resemble natural rain events and these measures are not comparables. And besides the intensity is related to the kinetic energy which determines the rainfall erosivity (Dunkerley D., 2008). A special attention must be paid to the experimental design and the understanding of the measurements obtained. The objective of this study is the calibration of simulated rain. In order to achieve this objective a rainfall simulator and disdrometer have been used. The first one is a nozzle type and its sprinkler system was located at different heights, three different spray nozzles supplied the water with known pressure. The simulated rainfall presented different intensities, drop diameters distribution and so different kinetic energy. The instrument of measurement for registering data is the disdrometer (Joss and Waldvogel, 1967) which provides the total number of impacts of raindrops, minute after minute, grouped in 20 classes according to their size which allows the real time measurements of the drop diameter distributions, kinetic energy per minute and intensity per minute. Disdrometer registers data in supposing drops fall down with terminal velocity but this velocity can reach up to 7-9 m of height in natural raindrop, depending on drop diameters. If the height of simulator is high enough the drops could recuperate their terminal velocities and their kinetic energies could be true. The nozzles were located to different heights in order to achieve these terminal velocities. These heights vary depending on the nozzles used, when the drops supplied by the nozzle are smaller the terminal velocity is reached sooner than when the drops are bigger. The physical characteristics of simulated rainfall in the three nozzles, intensity, drop diameter distributions and kinetic energy, are known and steady when the drops supplied by the nozzles reach terminal velocities.

Including local rainfall dynamics and uncertain boundary conditions into a 2-D regional-local flood modelling cascade

NASA Astrophysics Data System (ADS)

Bermúdez, María; Neal, Jeffrey C.; Bates, Paul D.; Coxon, Gemma; Freer, Jim E.; Cea, Luis; Puertas, Jerónimo

2016-04-01

Flood inundation models require appropriate boundary conditions to be specified at the limits of the domain, which commonly consist of upstream flow rate and downstream water level. These data are usually acquired from gauging stations on the river network where measured water levels are converted to discharge via a rating curve. Derived streamflow estimates are therefore subject to uncertainties in this rating curve, including extrapolating beyond the maximum observed ratings magnitude. In addition, the limited number of gauges in reach-scale studies often requires flow to be routed from the nearest upstream gauge to the boundary of the model domain. This introduces additional uncertainty, derived not only from the flow routing method used, but also from the additional lateral rainfall-runoff contributions downstream of the gauging point. Although generally assumed to have a minor impact on discharge in fluvial flood modeling, this local hydrological input may become important in a sparse gauge network or in events with significant local rainfall. In this study, a method to incorporate rating curve uncertainty and the local rainfall-runoff dynamics into the predictions of a reach-scale flood inundation model is proposed. Discharge uncertainty bounds are generated by applying a non-parametric local weighted regression approach to stage-discharge measurements for two gauging stations, while measured rainfall downstream from these locations is cascaded into a hydrological model to quantify additional inflows along the main channel. A regional simplified-physics hydraulic model is then applied to combine these inputs and generate an ensemble of discharge and water elevation time series at the boundaries of a local-scale high complexity hydraulic model. Finally, the effect of these rainfall dynamics and uncertain boundary conditions are evaluated on the local-scale model. Improvements in model performance when incorporating these processes are quantified using observed flood extent data and measured water levels from a 2007 summer flood event on the river Severn. The area of interest is a 7 km reach in which the river passes through the city of Worcester, a low water slope, subcritical reach in which backwater effects are significant. For this domain, the catchment area between flow gauging stations extends over 540 km2. Four hydrological models from the FUSE framework (Framework for Understanding Structural Errors) were set up to simulate the rainfall-runoff process over this area. At this regional scale, a 2-dimensional hydraulic model that solves the local inertial approximation of the shallow water equations was applied to route the flow, whereas the full form of these equations was solved at the local scale to predict the urban flow field. This nested approach hence allows an examination of water fluxes from the catchment to the building scale, while requiring short setup and computational times. An accurate prediction of the magnitude and timing of the flood peak was obtained with the proposed method, in spite of the unusual structure of the rain episode and the complexity of the River Severn system. The findings highlight the importance of estimating boundary condition uncertainty and local rainfall contribution for accurate prediction of river flows and inundation.

Surface runoff and soil erosion by difference of surface cover characteristics using by an oscillating rainfall simulator

NASA Astrophysics Data System (ADS)

Kim, J. K.; Kim, M. S.; Yang, D. Y.

2017-12-01

Sediment transfer within hill slope can be changed by the hydrologic characteristics of surface material on hill slope. To better understand sediment transfer of the past and future related to climate changes, studies for the changes of soil erosion due to hydrological characteristics changes by surface materials on hill slope are needed. To do so, on-situ rainfall simulating test was conducted on three different surface conditions, i.e. well covered with litter layer condition (a), undisturbed bare condition (b), and disturbed bare condition (c) and these results from rainfall simulating test were compared with that estimated using the Limburg Soil Erosion Model (LISEM). The result from the rainfall simulating tests showed differences in the infiltration rate (a > b > c) and the highest soil erosion rate was occurred on c condition. The result from model also was similar to those from rainfall simulating tests, however, the difference from the value of soil erosion rate between two results was quite large on b and c conditions. These results implied that the difference of surface conditions could change the surface runoff and soil erosion and the result from the erosion model might significantly underestimate on bare surface conditions rather than that from rainfall simulating test.

On the Numerical Study of Heavy Rainfall in Taiwan

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Ching-Sen; Chen, Yi-Leng; Jou, Ben Jong-Dao; Lin, Pay-Liam; Starr, David OC. (Technical Monitor)

2001-01-01

Heavy rainfall events are frequently observed over the western side of the CMR (central mountain range), which runs through Taiwan in a north-south orientation, in a southwesterly flow regime and over the northeastern side of the CMR in a northeasterly flow regime. Previous studies have revealed the mechanisms by which the heavy rainfall events are formed. Some of them have examined characteristics of the heavy rainfall via numerical simulations. In this paper, some of the previous numerical studies on heavy rainfall events around Taiwan during the Mei-Yu season (May and June), summer (non-typhoon cases) and autumn will be reviewed. Associated mechanisms proposed from observational studies will be reviewed first, and then characteristics of numerically simulated heavy rainfall events will be presented. The formation mechanisms of heavy rainfall from simulated results and from observational analysis are then compared and discussed. Based on these previous modeling studies, we will also discuss what are the major observations and modeling processes which will be needed for understanding the heavy precipitation in the future.

Rainfall estimates for hydrological models: Comparing rain gauge, radar and microwave link data as input for the Wageningen Lowland Runoff Simulator (WALRUS)

NASA Astrophysics Data System (ADS)

Brauer, Claudia; Overeem, Aart; Uijlenhoet, Remko

2015-04-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of differences in rainfall estimates on discharge simulations in a lowland catchment by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in the Hupsel Brook catchment. We used two automatic rain gauges with hourly resolution, located inside the catchment (the base run) and 30 km northeast. Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. Traditionally, the precipitation research community places emphasis on quantifying spatial errors and uncertainty, but for hydrological applications, temporal errors and uncertainty should be quantified as well. Its memory makes the hydrologic system sensitive to missed or badly timed rainfall events, but also emphasizes the effect of a bias in rainfall estimates. Systematic underestimation of rainfall by the uncorrected operational radar product leads to very dry model states and an increasing underestimation of discharge. Using the rain gauge 30 km northeast of the catchment yields good results for climatological studies, but not for forecasting individual floods. Simulating discharge using the maps derived from microwave link data and the gauge-adjusted radar product yields good results for both events and climatological studies. This indicates that these products can be used in catchments without gauges in or near the catchment. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. Improving rainfall measurements can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

Accounting for temporal variation in soil hydrological properties when simulating surface runoff on tilled plots

NASA Astrophysics Data System (ADS)

Chahinian, Nanée; Moussa, Roger; Andrieux, Patrick; Voltz, Marc

2006-07-01

Tillage operations are known to greatly influence local overland flow, infiltration and depressional storage by altering soil hydraulic properties and soil surface roughness. The calibration of runoff models for tilled fields is not identical to that of untilled fields, as it has to take into consideration the temporal variability of parameters due to the transient nature of surface crusts. In this paper, we seek the application of a rainfall-runoff model and the development of a calibration methodology to take into account the impact of tillage on overland flow simulation at the scale of a tilled plot (3240 m 2) located in southern France. The selected model couples the (Morel-Seytoux, H.J., 1978. Derivation of equations for variable rainfall infiltration. Water Resources Research. 14(4), 561-568). Infiltration equation to a transfer function based on the diffusive wave equation. The parameters to be calibrated are the hydraulic conductivity at natural saturation Ks, the surface detention Sd and the lag time ω. A two-step calibration procedure is presented. First, eleven rainfall-runoff events are calibrated individually and the variability of the calibrated parameters are analysed. The individually calibrated Ks values decrease monotonously according to the total amount of rainfall since tillage. No clear relationship is observed between the two parameters Sd and ω, and the date of tillage. However, the lag time ω increases inversely with the peakflow of the events. Fairly good agreement is observed between the simulated and measured hydrographs of the calibration set. Simple mathematical laws describing the evolution of Ks and ω are selected, while Sd is considered constant. The second step involves the collective calibration of the law of evolution of each parameter on the whole calibration set. This procedure is calibrated on 11 events and validated on ten runoff inducing and four non-runoff inducing rainfall events. The suggested calibration methodology seems robust and can be transposed to other gauged sites.

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Qian, J.-H.; Shie, C.-L.; Lau, W. K.-M.; Kakar, R.; Starr, David (Technical Monitor)

2002-01-01

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional scale model (with grid size of 20 km) and Goddard Cumulus Ensemble (GCE) model (with 1 km grid size) are used to perform multi-day integration to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during SCSMEX Sensitivity tests on various land surface models, sea surface temperature (SST) variations, and cloud processes are performed to understand the precipitation processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. Cloud processes can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. The GCE-model results captured many observed precipitation characteristics because it used a fine grid size. For example, the model simulated rainfall temporal variation compared quite well to the sounding-estimated rainfall. The results show there are more latent heat fluxes prior to the onset of the monsoon. However, more rainfall was simulated after the onset of the monsoon. This modeling study indicates the latent heat fluxes (or evaporation) have more of an impact on precipitation processes and rainfall in the regional climate model simulations than in the cloud-resolving model simulations. Research is underway to determine if the difference in the grid sizes or the moist processes used in these two models is responsible for the differing influence of surface fluxes an precipitation processes.

Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

NASA Astrophysics Data System (ADS)

Lucero, Omar A.; Rozas, Daniel

Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of this research could have further geographical validity.

Regionalization of subsurface stormflow parameters of hydrologic models: Up-scaling from physically based numerical simulations at hillslope scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ali, Melkamu; Ye, Sheng; Li, Hongyi

2014-07-19

Subsurface stormflow is an important component of the rainfall-runoff response, especially in steep forested regions. However; its contribution is poorly represented in current generation of land surface hydrological models (LSMs) and catchment-scale rainfall-runoff models. The lack of physical basis of common parameterizations precludes a priori estimation (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global models. This paper is aimed at deriving physically based parameterizations of the storage-discharge relationship relating to subsurface flow. These parameterizations are derived through a two-step up-scaling procedure: firstly, through simulations with a physically based (Darcian) subsurfacemore » flow model for idealized three dimensional rectangular hillslopes, accounting for within-hillslope random heterogeneity of soil hydraulic properties, and secondly, through subsequent up-scaling to the catchment scale by accounting for between-hillslope and within-catchment heterogeneity of topographic features (e.g., slope). These theoretical simulation results produced parameterizations of the storage-discharge relationship in terms of soil hydraulic properties, topographic slope and their heterogeneities, which were consistent with results of previous studies. Yet, regionalization of the resulting storage-discharge relations across 50 actual catchments in eastern United States, and a comparison of the regionalized results with equivalent empirical results obtained on the basis of analysis of observed streamflow recession curves, revealed a systematic inconsistency. It was found that the difference between the theoretical and empirically derived results could be explained, to first order, by climate in the form of climatic aridity index. This suggests a possible codependence of climate, soils, vegetation and topographic properties, and suggests that subsurface flow parameterization needed for ungauged locations must account for both the physics of flow in heterogeneous landscapes, and the co-dependence of soil and topographic properties with climate, including possibly the mediating role of vegetation.« less

Attribution of extreme precipitation in the lower reaches of the Yangtze River during May 2016

NASA Astrophysics Data System (ADS)

Li, Chunxiang; Tian, Qinhua; Yu, Rong; Zhou, Baiquan; Xia, Jiangjiang; Burke, Claire; Dong, Buwen; Tett, Simon F. B.; Freychet, Nicolas; Lott, Fraser; Ciavarella, Andrew

2018-01-01

May 2016 was the third wettest May on record since 1961 over central eastern China based on station observations, with total monthly rainfall 40% more than the climatological mean for 1961-2013. Accompanying disasters such as waterlogging, landslides and debris flow struck part of the lower reaches of the Yangtze River. Causal influence of anthropogenic forcings on this event is investigated using the newly updated Met Office Hadley Centre system for attribution of extreme weather and climate events. Results indicate that there is a significant increase in May 2016 rainfall in model simulations relative to the climatological period, but this increase is largely attributable to natural variability. El Niño years have been found to be correlated with extreme rainfall in the Yangtze River region in previous studies—the strong El Niño of 2015-2016 may account for the extreme precipitation event in 2016. However, on smaller spatial scales we find that anthropogenic forcing has likely played a role in increasing the risk of extreme rainfall to the north of the Yangtze and decreasing it to the south.

Comparison between fully distributed model and semi-distributed model in urban hydrology modeling

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Giangola-Murzyn, Agathe; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe

2013-04-01

Water management in urban areas is becoming more and more complex, especially because of a rapid increase of impervious areas. There will also possibly be an increase of extreme precipitation due to climate change. The aims of the devices implemented to handle the large amount of water generate by urban areas such as storm water retention basins are usually twofold: ensure pluvial flood protection and water depollution. These two aims imply opposite management strategies. To optimize the use of these devices there is a need to implement urban hydrological models and improve fine-scale rainfall estimation, which is the most significant input. In this paper we suggest to compare two models and their sensitivity to small-scale rainfall variability on a 2.15 km2 urban area located in the County of Val-de-Marne (South-East of Paris, France). The average impervious coefficient is approximately 34%. In this work two types of models are used. The first one is CANOE which is semi-distributed. Such models are widely used by practitioners for urban hydrology modeling and urban water management. Indeed, they are easily configurable and the computation time is reduced, but these models do not take fully into account either the variability of the physical properties or the variability of the precipitations. An alternative is to use distributed models that are harder to configure and require a greater computation time, but they enable a deeper analysis (especially at small scales and upstream) of the processes at stake. We used the Multi-Hydro fully distributed model developed at the Ecole des Ponts ParisTech. It is an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. Four heavy rainfall events that occurred between 2009 and 2011 are analyzed. The data comes from the Météo-France radar mosaic and the resolution is 1 km in space and 5 min in time. The closest radar of the Météo-France network is a C-band one located at 37 km West. In this work we compare the hydrological response of two models for the 4 rainfall events first with the available radar data. Then a particular focus is made on the impact of small-scale unmeasured rainfall variability (i.e. occurring at scales below the available one). More precisely scaling properties of rainfall are used to generate an ensemble of downscaled rainfall fields (simply by continuing the underlying cascade process whose relevant parameters are estimated on the available range of scales). An ensemble of hydrological responses is then simulated, and the variability within it analyzed. It appears that the associated uncertainty is significant and should be taken into account. Finally we will discuss the interest of deploying X-band radars (which provide an hectometric resolution) in urban environment and the potential benefits of using these models and small-scale rainfall data for the management of sewerage and retentions basin. Further analysis on these issues will be carried out next year with the installation of an X-band radar near Marne-la-Vallée (located at roughly 10 Km of the studied catchment) in the framework of the RainGain project (European project financed by the Interreg IVB funds).

Chemistry of through-fall and stem-flow leachate following rainfall simulation over pinyon and juniper

USDA-ARS?s Scientific Manuscript database

We hypothesized that leachate from pinyon and juniper canopies, following rainfall events, may contribute sizable levels of solutes and C to the soil surface. We quantified solutes and dissolved carbon in stem-flow (SF) and through-fall (TF) following replicated rainfall simulation events in a pinyo...

Temporal and spatial variability of rainfall over Greece

NASA Astrophysics Data System (ADS)

Markonis, Y.; Batelis, S. C.; Dimakos, Y.; Moschou, E.; Koutsoyiannis, D.

2017-10-01

Recent studies have showed that there is a significant decrease in rainfall over Greece during the last half of the pervious century, following an overall decrease of the precipitation at the eastern Mediterranean. However, during the last decade an increase in rainfall was observed in most regions of the country, contrary to the general circulation climate models forecasts. An updated high-resolution dataset of monthly sums and annual daily maxima records derived from 136 stations during the period 1940-2012 allowed us to present some new evidence for the observed change and its statistical significance. The statistical framework used to determine the significance of the slopes in annual rain was not limited to the time independency assumption (Mann-Kendall test), but we also investigated the effect of short- and long-term persistence through Monte Carlo simulation. Our findings show that (a) change occurs in different scales; most regions show a decline since 1950, an increase since 1980 and remain stable during the last 15 years; (b) the significance of the observed decline is highly dependent to the statistical assumptions used; there are indications that the Mann-Kendall test may be the least suitable method; and (c) change in time is strongly linked with the change in space; for scales below 40 years, relatively close regions may develop even opposite trends, while in larger scales change is more uniform.

Development of a flash flood warning system based on real-time radar data and process-based erosion modelling

NASA Astrophysics Data System (ADS)

Schindewolf, Marcus; Kaiser, Andreas; Buchholtz, Arno; Schmidt, Jürgen

2017-04-01

Extreme rainfall events and resulting flash floods led to massive devastations in Germany during spring 2016. The study presented aims on the development of a early warning system, which allows the simulation and assessment of negative effects on infrastructure by radar-based heavy rainfall predictions, serving as input data for the process-based soil loss and deposition model EROSION 3D. Our approach enables a detailed identification of runoff and sediment fluxes in agricultural used landscapes. In a first step, documented historical events were analyzed concerning the accordance of measured radar rainfall and large scale erosion risk maps. A second step focused on a small scale erosion monitoring via UAV of source areas of heavy flooding events and a model reconstruction of the processes involved. In all examples damages were caused to local infrastructure. Both analyses are promising in order to detect runoff and sediment delivering areas even in a high temporal and spatial resolution. Results prove the important role of late-covering crops such as maize, sugar beet or potatoes in runoff generation. While e.g. winter wheat positively affects extensive runoff generation on undulating landscapes, massive soil loss and thus muddy flows are observed and depicted in model results. Future research aims on large scale model parameterization and application in real time, uncertainty estimation of precipitation forecast and interface developments.

Application and comparison of the SCS-CN-based rainfall-runoff model in meso-scale watershed and field scale

NASA Astrophysics Data System (ADS)

Luo, L.; Wang, Z.

2010-12-01

Soil Conservation Service Curve Number (SCS-CN) based hydrologic model, has widely been used for agricultural watersheds in recent years. However, there will be relative error when applying it due to differentiation of geographical and climatological conditions. This paper introduces a more adaptable and propagable model based on the modified SCS-CN method, which specializes into two different scale cases of research regions. Combining the typical conditions of the Zhanghe irrigation district in southern part of China, such as hydrometeorologic conditions and surface conditions, SCS-CN based models were established. The Xinbu-Qiao River basin (area =1207 km2) and the Tuanlin runoff test area (area =2.87 km2)were taken as the study areas of basin scale and field scale in Zhanghe irrigation district. Applications were extended from ordinary meso-scale watershed to field scale in Zhanghe paddy field-dominated irrigated . Based on actual measurement data of land use, soil classification, hydrology and meteorology, quantitative evaluation and modifications for two coefficients, i.e. preceding loss and runoff curve, were proposed with corresponding models, table of CN values for different landuse and AMC(antecedent moisture condition) grading standard fitting for research cases were proposed. The simulation precision was increased by putting forward a 12h unit hydrograph of the field area, and 12h unit hydrograph were simplified. Comparison between different scales show that it’s more effectively to use SCS-CN model on field scale after parameters calibrated in basin scale These results can help discovering the rainfall-runoff rule in the district. Differences of established SCS-CN model's parameters between the two study regions are also considered. Varied forms of landuse and impacts of human activities were the important factors which can impact the rainfall-runoff relations in Zhanghe irrigation district.

Evaluation of satellite and simulated rainfall products for hydrological applications in the Notwane catchment, Botswana

NASA Astrophysics Data System (ADS)

Kenabatho, P. K.; Parida, B. P.; Moalafhi, D. B.

2017-08-01

In semi-arid catchments, hydrological modeling, water resources planning and management are hampered by insufficient spatial rainfall data which is usually derived from limited rain gauge networks. Satellite products are potential candidates to augment the limited spatial rainfall data in these areas. In this paper, the utility of the Tropical Rainfall Measuring Mission (TRMM) product (3B42 v7) is evaluated using data from the Notwane catchment in Botswana. In addition, rainfall simulations obtained from a multi-site stochastic rainfall model based on the generalised linear models (GLMs) were used as additional spatial rainfall estimates. These rainfall products were compared to the observed rainfall data obtained from six (6) rainfall stations available in the catchment for the period 1998-2012. The results show that in general the two approaches produce reasonable spatial rainfall estimates. However, the TRMM products provided better spatial rainfall estimates compared to the GLM rainfall outputs on an average, as more than 90% of the monthly rainfall variations were explained by the TRMM compared to 80% from the GLMs. However, there is still uncertainty associated mainly with limited rainfall stations, and the inability of the two products to capture unusually high rainfall values in the data sets. Despite this observation, rainfall indices computed to further assess the daily rainfall products (i.e. rainfall occurrence and amounts, length of dry spells) were adequately represented by the TRMM data compared to the GLMs. Performance from the GLMs is expected to improve with addition of further rainfall predictors. A combination of these rainfall products allows for reasonable spatial rainfall estimates and temporal (short term future) rainfall simulations from the TRMM and GLMs, respectively. The results have significant implications on water resources planning and management in the catchment which has, for the past three years, been experiencing prolonged droughts as shown by the drying of Gaborone dam (currently at a record low of 1.6% full), which is the main source of water supply to the city of Gaborone and neighbouring townships in Botswana.

A cellular automata approach for modeling surface water runoff

NASA Astrophysics Data System (ADS)

Jozefik, Zoltan; Nanu Frechen, Tobias; Hinz, Christoph; Schmidt, Heiko

2015-04-01

This abstract reports the development and application of a two-dimensional cellular automata based model, which couples the dynamics of overland flow, infiltration processes and surface evolution through sediment transport. The natural hill slopes are represented by their topographic elevation and spatially varying soil properties infiltration rates and surface roughness coefficients. This model allows modeling of Hortonian overland flow and infiltration during complex rainfall events. An advantage of the cellular automata approach over the kinematic wave equations is that wet/dry interfaces that often appear with rainfall overland flows can be accurately captured and are not a source of numerical instabilities. An adaptive explicit time stepping scheme allows for rainfall events to be adequately resolved in time, while large time steps are taken during dry periods to provide for simulation run time efficiency. The time step is constrained by the CFL condition and mass conservation considerations. The spatial discretization is shown to be first-order accurate. For validation purposes, hydrographs for non-infiltrating and infiltrating plates are compared to the kinematic wave analytic solutions and data taken from literature [1,2]. Results show that our cellular automata model quantitatively accurately reproduces hydrograph patterns. However, recent works have showed that even through the hydrograph is satisfyingly reproduced, the flow field within the plot might be inaccurate [3]. For a more stringent validation, we compare steady state velocity, water flux, and water depth fields to rainfall simulation experiments conducted in Thies, Senegal [3]. Comparisons show that our model is able to accurately capture these flow properties. Currently, a sediment transport and deposition module is being implemented and tested. [1] M. Rousseau, O. Cerdan, O. Delestre, F. Dupros, F. James, S. Cordier. Overland flow modeling with the Shallow Water Equation using a well balanced numerical scheme: Adding efficiency or sum more complexity?. 2012. [2] Fritz R. Fiedler, J. A. Ramirez. A numerical method for simulating discontinuous shallow flow over an infiltrating surface. In. J. Numer. Mech. Fluids 200: 32: 219-240. [3] C. Mügler, O. Planchon, J. Patin, S. Weill, N. Silvera, P. Richard, E. Mouche. Comparison of Roughness models to simulate overland flow and tracer transport experiments under simulated rainfall at plot scale. Journal of Hydrology. 402 (2011) 25-40.

Prognostic Aspects of Sub-seasonal Rainfall Characteristics using the Outputs of General Circulation Model: An Application of Statistical Downscaling and Temporal Disaggregation

NASA Astrophysics Data System (ADS)

Singh, A.; Mohanty, U. C.; Ghosh, K.

2015-12-01

Most regions of India experience varied rainfall duration during the southwest monsoon, changes in which exhibit major impact not only agriculture, but also other sectors like hydrology, agriculture, food and fodder storage etc. In addition, changes in sub-seasonal rainfall characteristics highly impact the rice production. As part of the endeavor seasonal climate outlook, as well as information for weather within climate may be helpful for advance planning and risk management in agriculture. The General Circulation Model (GCM) provide an alternative to gather information for weather within climate but variability is very low in comparison to observation. On the other hand, the spatial resolution of GCM predicted rainfall is not found at the observed station/grid point. To tackle the problem, initially a statistical downscaling over 19 station of Odisha state is undertaken using the atmospheric parameters predicted by a GCM (NCEP-CFSv2). For the purpose, an extended domain is taken for analyzing the significant zone for the atmospheric parameters like zonal wind at 850hPa, Sea Surface Temperature (SST), geopotential height. A statistical model using the pattern projection method is further developed based on empirical orthogonal function. The downscaled rainfall is found better in association with station observation in comparison to raw GCM prediction in view of deterministic and probabilistic skill measure. Further, the sub-seasonal and seasonal forecast from the GCMs can be used at different time steps for risk management. Therefore, downscaled seasonal/monthly rainfall is further converted to sub-seasonal/daily time scale using a non-homogeneous markov model. The simulated weather sequences are further compared with the observed sequence in view of categorical rainfall events. The outcomes suggest that the rainfall amount are overestimated for excess rainfall and henceforth larger excess rainfall events can be realized. The skill for prediction of rainfall events corresponding to lower thresholds is found higher. A detail discussion regarding skill of spatial downscale rainfall at observed stations and its further representation of sub-seasonal characteristics (spells, less rainfall, heavy rainfall, and moderate rainfall events) of rainfall for disaggregated outputs will be presented.

Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

NASA Astrophysics Data System (ADS)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

Spectral analysis of temporal non-stationary rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Chang, Ching-Min; Yeh, Hund-Der

2018-04-01

This study treats the catchment as a block box system with considering the rainfall input and runoff output being a stochastic process. The temporal rainfall-runoff relationship at the catchment scale is described by a convolution integral on a continuous time scale. Using the Fourier-Stieltjes representation approach, a frequency domain solution to the convolution integral is developed to the spectral analysis of runoff processes generated by temporal non-stationary rainfall events. It is shown that the characteristic time scale of rainfall process increases the runoff discharge variability, while the catchment mean travel time constant plays the role in reducing the variability of runoff discharge. Similar to the behavior of groundwater aquifers, catchments act as a low-pass filter in the frequency domain for the rainfall input signal.

Seasonal variations of soil erosion in UK under climate change: simulations with the use of high-resolution regional climatic models

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Kendon, Elizabeth; Constantine, José Antonio; Schindewolf, Marcus; Hall, Ian

2017-04-01

Climate change is expected to have a significant impact on the hydrological cycle, twenty-first century climate change simulations for Great Britain forecast an increase of surface runoff and flooding frequency. Once quality and resolution of the simulated rainfall deeply influence the results, we adopted rainfall simulations issued of a high-resolution climate model recently carried out for extended periods (13 years for present-day and future periods 2100) at 1.5 km grid scale over the south of the United Kingdom (simulations, which for the future period use the Intergovernmental Panel on Climate Change RCP 8.5 scenario, Kendon et al., 2014). We simulated soil erosion with 3D soil erosion model Schmidt (1990) on two catchments of Great Britain: the Rother catchment (350 km2) in West Sussex, England, because it has reported some of the most erosive events observed during the last 50 years in the UK, and the Conwy catchment (628 Km2) in North Wales, which is extremely resilient to soil erosion because of the abundant natural vegetation. Estimation of changes in soil moisture, saturation deficit as well as vegetation cover at daily time step have been done with the Joint UK Land Environment Simulator (JULES) (Best et al, 2011). Our results confirm the Rother catchment is the most erosive, while the Conwy catchment is the more resilient to soil erosion. Sediment production is perceived increase in both cases for the end of the century (27% and 50%, respectively). Seasonal disaggregation of the results revels that, while the most part of soil erosion is produced in winter months (DJF), the higher soil erosion variability for future periods is observed in summer (JJA). This behaviour is supported by the rainfall simulation analyse which highlighted this dual behaviour in precipitations.

The Three Gorges Dam Affects Regional Precipitation

NASA Technical Reports Server (NTRS)

Wu, Liguang; Zhang, Qiang; Jiang, Zhihong

2006-01-01

Issues regarding building large-scale dams as a solution to power generation and flood control problems have been widely discussed by both natural and social scientists from various disciplines, as well as the policy-makers and public. Since the Chinese government officially approved the Three Gorges Dam (TGD) projects, this largest hydroelectric project in the world has drawn a lot of debates ranging from its social and economic to climatic impacts. The TGD has been partially in use since June 2003. The impact of the TGD is examined through analysis of the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) rainfall rate and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and high-resolution simulation using the Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) fifth-generation Mesoscale Model (MM5). The independent satellite data sets and numerical simulation clearly indicate that the land use change associated with the TGD construction has increased the precipitation in the region between Daba and Qinling mountains and reduced the precipitation in the vicinity of the TGD after the TGD water level abruptly rose from 66 to 135 m in June 2003. This study suggests that the climatic effect of the TGD is on the regional scale (approx.100 km) rather than on the local scale (approx.10 km) as projected in previous studies.

[Canopy interception of sub-alpine dark coniferous communities in western Sichuan, China].

PubMed

Lü, Yu-liang; Liu, Shi-rong; Sun, Peng-sen; Liu, Xing-liang; Zhang, Rui-pu

2007-11-01

Based on field measurements of throughfall and stemflow in combination with climatic data collected from the meteorological station adjacent to the studied sub-alpine dark coniferous forest in Wolong, Sichuan Province, canopy interception of sub-alpine dark coniferous forests was analyzed and modeled at both stand scale and catchment scale. The results showed that monthly interception rate of Fargesia nitida, Bashania fangiana--Abies faxoniana old-growth ranged from 33% Grass to 72%, with the average of 48%. In growing season, there was a linear or powerful or exponential relationship between rainfall and interception an. a negative exponential relationship between rainfall and interception rate. The mean maximum canopy interception by the vegetation in the catchment of in.44 km was 1.74 ment and the significant differences among the five communities occurred in the following sequence: Moss-Fargesia nitida, Bashan afanglana-A. faxoniana stand > Grass-F. nitida, B. fangiana-A. faxoniana stand > Moss-Rhododendron spp.-A. faxoniana stand > Grass-Rh. spp.-A. faxoniana stand > Rh. spp. shrub. In addition, a close linear relationship existed between leaf area index (LAI) and maximum canopy interception. The simulated value of canopy interception rate, maximum canopy interception rate and addition interception rate of the vegetation in the catchment were 39%, 25% and 14%, respectively. Simulation of the canopy interception model was better at the overall growing season scale, that the mean relative error was 9%-14%.

Aircraft Observations of Soil Hydrological Influence on the Atmosphere in Northern India

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Barton, Emma J.; Belusic, Danijel; Böing, Steven J.; Hunt, Kieran M. R.; Mitra, Ashis K.; Parker, Douglas J.; Turner, Andrew G.

2017-04-01

India is considered to be a region of the world where the influence of land surface fluxes of sensible and latent heat play an important role in regional weather and climate. Indian rainfall simulations in GCMs are known to be particularly sensitive to soil moisture. However, in a monsoon region where seasonal convective rainfall dominates, it is a big challenge for GCMs to capture, on the one hand, a realistic depiction of surface fluxes during wetting up and drying down at seasonal and sub-seasonal scales, and on the other, the sensitivity of convective rainfall and regional circulations to space-time fluctuations in land surface fluxes. On top of this, most GCMs and operational atmospheric forecast models don't explicitly consider irrigation. In the Indo-Gangetic plains of the Indian sub-continent, irrigated agriculture has become the dominant land use. Irrigation suppresses temporal flux variability for much of the year, and at the same time enhances spatial heterogeneity. One of the key objectives of the Anglo-Indian Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) collaborative project is to better understand the coupling between the land surface and the Indian summer monsoon, and build this understanding into improved prediction of rainfall on multiple time and space scales. During June and July 2016, a series of research flights was performed across the sub-continent using the NERC/Met Office BAe146 aircraft. Here we will present results for a case study from a flight on 30th June which sampled the Planetary Boundary Layer (PBL) on a 700 km low level transect, from the semi-arid region of Rajasthan eastwards into the extensively irrigated state of Uttar Pradesh. As well as crossing different land uses, the flight also sampled mesoscale regions with contrasting recent rainfall conditions. Here we will show how variations in surface hydrology, driven by both irrigation and rainfall, influence the temperature, humidity and winds in the PBL. These unique observations will provide a powerful tool for understanding the dominant land-atmosphere coupling mechanisms operating on a range of multiple length scales, and which help to shape the Indian monsoon.

Drought Early Warning and Agro-Meteorological Risk Assessment using Earth Observation Rainfall Datasets and Crop Water Budget Modelling

NASA Astrophysics Data System (ADS)

Tarnavsky, E.

2016-12-01

The water resources satisfaction index (WRSI) model is widely used in drought early warning and food security analyses, as well as in agro-meteorological risk management through weather index-based insurance. Key driving data for the model is provided from satellite-based rainfall estimates such as ARC2 and TAMSAT over Africa and CHIRPS globally. We evaluate the performance of these rainfall datasets for detecting onset and cessation of rainfall and estimating crop production conditions for the WRSI model. We also examine the sensitivity of the WRSI model to different satellite-based rainfall products over maize growing regions in Tanzania. Our study considers planting scenarios for short-, medium-, and long-growing cycle maize, and we apply these for 'regular' and drought-resistant maize, as well as with two different methods for defining the start of season (SOS). Simulated maize production estimates are compared against available reported production figures at the national and sub-national (province) levels. Strengths and weaknesses of the driving rainfall data, insights into the role of the SOS definition method, and phenology-based crop yield coefficient and crop yield reduction functions are discussed in the context of space-time drought characteristics. We propose a way forward for selecting skilled rainfall datasets and discuss their implication for crop production monitoring and the design and structure of weather index-based insurance products as risk transfer mechanisms implemented across scales for smallholder farmers to national programmes.

Changing frequency of flooding in Bangladesh: Is the wettest place on Earth getting wetter?

NASA Astrophysics Data System (ADS)

Haustein, K.; Uhe, P.; Rimi, R.; Islam, A. S.; Otto, F. E. L.

2017-12-01

Human influence on the Asian monsoon is exerted by two counteracting forces, (1) anthropogenic warming due to the influence of increasing Greenhouse Gas (GHG) emissions and (2) radiative cooling due to increased amounts of anthropogenic aerosols. GHG emissions tend to intensify the water cycle and increase monsoon precipitation, whereas aerosols are considered to have the opposite effect. On larger scales, aerosols may be responsible for meridional circulation anomalies as well as direct cooling effects, with an associated tendency for drier monsoon seasons that compensate a change towards wetter conditions in a purely GHG-driven scenario. On regional scales, aerosols weaken the thermal contrast between land and ocean which acts to inhibit the monsoon too. As a result, neither observations nor model simulations that consider all human influences suggest clear changes in extreme precipitation at present. In actual reality we are essentially committed to more rainfall extremes already as aerosol pollution will eventually be reduced regardless of future GHG emissions. Thus we argue that it is crucial to assess the risk related to removing anthropogenic aerosols from the current world as opposed to standard experiments that use projected climate scenarios. We present results from on analysis of extreme precipitation that led to the Bangladesh floods in summer 2016. Since the Meghalaya Hills are the major contributor to flood waters in Bangladesh, we focus on this region, despite slightly higher rainfall anomalies further west. More specifically, we primarily analyze the grid point representing Cherrapunji, also known to be the wettest place on Earth (situated on the southern flank of Meghalaya Hills). We use the weather@home HadAM3P model at 50km spatial resolution. Our model results generally support the notion that rainfall extremes in Cherrapunji might have become more likely already. Mean rainfall is slightly lowered, but 21-day maximum rainfall under current "allforcing" conditions has occurred more often compared to the counterfactual world. While the 2016 rainfall event was not extreme, our results indicate that such flood-inducing rainfall will likely become more frequent without aerosols. In other words, mean rainfall trends could reverse, with considerably increased risks for more future flooding.

Evaluation of Rainfall-Runoff Models for Mediterranean Subcatchments

NASA Astrophysics Data System (ADS)

Cilek, A.; Berberoglu, S.; Donmez, C.

2016-06-01

The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA), a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

The development of an hourly gridded rainfall product for hydrological applications in England and Wales

NASA Astrophysics Data System (ADS)

Liguori, Sara; O'Loughlin, Fiachra; Souvignet, Maxime; Coxon, Gemma; Freer, Jim; Woods, Ross

2014-05-01

This research presents a newly developed observed sub-daily gridded precipitation product for England and Wales. Importantly our analysis specifically allows a quantification of rainfall errors from grid to the catchment scale, useful for hydrological model simulation and the evaluation of prediction uncertainties. Our methodology involves the disaggregation of the current one kilometre daily gridded precipitation records available for the United Kingdom[1]. The hourly product is created using information from: 1) 2000 tipping-bucket rain gauges; and 2) the United Kingdom Met-Office weather radar network. These two independent datasets provide rainfall estimates at temporal resolutions much smaller than the current daily gridded rainfall product; thus allowing the disaggregation of the daily rainfall records to an hourly timestep. Our analysis is conducted for the period 2004 to 2008, limited by the current availability of the datasets. We analyse the uncertainty components affecting the accuracy of this product. Specifically we explore how these uncertainties vary spatially, temporally and with climatic regimes. Preliminary results indicate scope for improvement of hydrological model performance by the utilisation of this new hourly gridded rainfall product. Such product will improve our ability to diagnose and identify structural errors in hydrological modelling by including the quantification of input errors. References [1] Keller V, Young AR, Morris D, Davies H (2006) Continuous Estimation of River Flows. Technical Report: Estimation of Precipitation Inputs. in Agency E (ed.). Environmental Agency.

Trend and variability in western and central Africa streamflow, and their relation to climate variability between 1950 and 2010

NASA Astrophysics Data System (ADS)

Sidibe, Moussa; Dieppois, Bastien; Mahé, Gil; Paturel, Jean-Emmanuel; Rouché, Nathalie; Amoussou, Ernest; Anifowose, Babatunde; Lawler, Damian

2017-04-01

Unprecedented drought episodes that struck western and central Africa between the late 1960s and 1980s. This triggered many studies investigating rainfall variability and its impacts on food production systems. However, most studies were focused at the catchment scale. In this study, we examine how rainfall variability has impacted on river flow at the subcontinental scale between 1950 and 2010, as well as the key large-scale controls on this relationship. For the first time, we establish a complete, gap-filled, monthly streamflow data set, which extends from 1950 to 2010, over the western and central African region. To achieve this, we used linear regression modelling across and between 600 flow gauging stations (see initial database information at http://www.hydrosciences.fr/sierem/index_en.htm). Streamflow trend and variability are then seasonally assessed at this subcontinental scale and compared to those observed in three different rainfall data sets (i.e. CRU TS3.24, GPCC V7, IRD-HSM). Long-term trends and variability in streamflow are mainly consistent with trends in rainfall. However, these relationships may have been moderated by: i) changes in land use; and ii) contributions from groundwater resources. In particular, we note that the recent post 1990s partial recovery in Sahel rainfall could have, at least partially, positively impacted river flows (e.g. the Senegal and Niger rivers). Using multi-temporal trend and continuous wavelet analysis, the time-evolution of western and central African river flows are analysed, and are all characterized by very strong decadal fluctuations, which can be interpreted as modulations in the baseflow. These decadal fluctuations, which are also significantly detected in rainfall, are likely related to large-scale sea-surface temperature (SST) anomaly patterns, such as the tropical Atlantic SST variability, the Atlantic Multidecadal Oscillation, the Interdecadal Pacific Oscillation and/or the Pacific Decadal Oscillation. Furthermore, hitherto-poorly understood hydroclimatic processes related to these teleconnections at decadal timescales will be examined in this study. Influences of the catchment properties (e.g. size, shape, vegetation and landuse cover, soil type, ground-water level, direction of stream flow across climate zones) on these decadal fluctuations in river flows will also be assessed. This study therefore aims to improve the ability of current regional and global climate models to simulate such ranges of variability, to significantly improve regional hydroclimate understanding, as a means for improving the development of future scenarios for water resources in western and central Africa.

Rainfall-induced release of microbes from manure: model development, parameter estimation, and uncertainty evaluation on small plots

USDA-ARS?s Scientific Manuscript database

A series of simulated rainfall-runoff experiments with applications of different manure types (cattle solid pats, poultry dry litter, swine slurry) were conducted across four seasons on a field containing 36 plots (0.75 × 2 m each), resulting in 144 rainfall-runoff events. Simulating time-varying re...

Building rainfall thresholds for large-scales landslides by extracting occurrence time of landslides from seismic records

NASA Astrophysics Data System (ADS)

Yen, Hsin-Yi; Lin, Guan-Wei

2017-04-01

Understanding the rainfall condition which triggers mass moment on hillslope is the key to forecast rainfall-induced slope hazards, and the exact time of landslide occurrence is one of the basic information for rainfall statistics. In the study, we focused on large-scale landslides (LSLs) with disturbed area larger than 10 ha and conducted a string of studies including the recognition of landslide-induced ground motions and the analyses of different terms of rainfall thresholds. More than 10 heavy typhoons during the periods of 2005-2014 in Taiwan induced more than hundreds of LSLs and provided the opportunity to characterize the rainfall conditions which trigger LSLs. A total of 101 landslide-induced seismic signals were identified from the records of Taiwan seismic network. These signals exposed the occurrence time of landslide to assess rainfall conditions. Rainfall analyses showed that LSLs occurred when cumulative rainfall exceeded 500 mm. The results of rainfall-threshold analyses revealed that it is difficult to distinct LSLs from small-scale landslides (SSLs) by the I-D and R-D methods, but the I-R method can achieve the discrimination. Besides, an enhanced three-factor threshold considering deep water content was proposed as the rainfall threshold for LSLs.

A Decade-Long European-Scale Convection-Resolving Climate Simulation on GPUs

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.

2016-12-01

Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer designs that involve conventional multi-core CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation over Europe using the GPU-enabled COSMO version on a computational domain with 1536x1536x60 gridpoints. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss some of the advantages and prospects from using GPUs, and focus on the performance of the convection-resolving modeling approach on the European scale. Specifically we investigate the organization of convective clouds and on validate hourly rainfall distributions with various high-resolution data sets.

Final Technical Report for "Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, A.W.; Ghil, M.; Kravtsov, K.

2011-04-08

This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs,more » we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes. Each of these project components is elaborated on below, followed by a list of publications resulting from the grant.« less

Final Technical Report for "Collaborative Research. Regional climate-change projections through next-generation empirical and dynamical models"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kravtsov, S.; Robertson, Andrew W.; Ghil, Michael

2011-04-08

This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs,more » we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes. Each of these project components is elaborated on below, followed by a list of publications resulting from the grant.« less

Study of sediment movement in an irrigated maize-cotton system combining rainfall simulations, sediment tracers and soil erosion models

NASA Astrophysics Data System (ADS)

Guzmán, Gema; Laguna, Ana; Cañasveras, Juan Carlos; Boulal, Hakim; Barrón, Vidal; Gómez-Macpherson, Helena; Giráldez, Juan Vicente; Gómez, José Alfonso

2015-05-01

Although soil erosion is one of the main threats to agriculture sustainability in many areas of the world, its processes are difficult to measure and still need a better characterization. The use of iron oxides as sediment tracers, combined with erosion and mixing models opens up a pathway for improving the knowledge of the erosion and redistribution of soil, determining sediment sources and sinks. In this study, magnetite and a multivariate mixing model were used in rainfall simulations at the micro-plot scale to determine the source of the sediment at different stages of a furrow-ridge system both with (+T) and without (-T) wheel tracks. At a plot scale, magnetite, hematite and goethite combined with two soil erosion models based on the kinematic wave approach were used in a sprinkler irrigation test to study trends in sediment transport and tracer dynamics along furrow lengths under a wide range of scenarios. In the absence of any stubble cover, sediment contribution from the ridges was larger than the furrow bed one, almost 90%, while an opposite trend was observed with stubble, with a smaller contribution from the ridge (32%) than that of the bed, at the micro-plot trials. Furthermore, at a plot scale, the tracer concentration analysis showed an exponentially decreasing trend with the downstream distance both for sediment detachment along furrows and soil source contribution from tagged segments. The parameters of the distributed model KINEROS2 have been estimated using the PEST Model to obtain a more accurate evaluation. Afterwards, this model was used to simulate a broad range of common scenarios of topography and rainfall from commercial farms in southern Spain. Higher slopes had a significant influence on sediment yields while long furrow distances allowed a more efficient water use. For the control of runoff, and therefore soil loss, an equilibrium between irrigation design (intensity, duration, water pattern) and hydric needs of the crops should be defined in order to establish a sustainable management strategy.

Tropical cyclone rainfall area controlled by relative sea surface temperature

PubMed Central

Lin, Yanluan; Zhao, Ming; Zhang, Minghua

2015-01-01

Tropical cyclone rainfall rates have been projected to increase in a warmer climate. The area coverage of tropical cyclones influences their impact on human lives, yet little is known about how tropical cyclone rainfall area will change in the future. Here, using satellite data and global atmospheric model simulations, we show that tropical cyclone rainfall area is controlled primarily by its environmental sea surface temperature (SST) relative to the tropical mean SST (that is, the relative SST), while rainfall rate increases with increasing absolute SST. Our result is consistent with previous numerical simulations that indicated tight relationships between tropical cyclone size and mid-tropospheric relative humidity. Global statistics of tropical cyclone rainfall area are not expected to change markedly under a warmer climate provided that SST change is relatively uniform, implying that increases in total rainfall will be confined to similar size domains with higher rainfall rates. PMID:25761457

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

NASA Astrophysics Data System (ADS)

Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

2018-03-01

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

SWAT use of gridded observations for simulating runoff - a Vietnam river basin study

NASA Astrophysics Data System (ADS)

Vu, M. T.; Raghavan, S. V.; Liong, S. Y.

2012-08-01

Many research studies that focus on basin hydrology have applied the SWAT model using station data to simulate runoff. But over regions lacking robust station data, there is a problem of applying the model to study the hydrological responses. For some countries and remote areas, the rainfall data availability might be a constraint due to many different reasons such as lacking of technology, war time and financial limitation that lead to difficulty in constructing the runoff data. To overcome such a limitation, this research study uses some of the available globally gridded high resolution precipitation datasets to simulate runoff. Five popular gridded observation precipitation datasets: (1) Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE), (2) Tropical Rainfall Measuring Mission (TRMM), (3) Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN), (4) Global Precipitation Climatology Project (GPCP), (5) a modified version of Global Historical Climatology Network (GHCN2) and one reanalysis dataset, National Centers for Environment Prediction/National Center for Atmospheric Research (NCEP/NCAR) are used to simulate runoff over the Dak Bla river (a small tributary of the Mekong River) in Vietnam. Wherever possible, available station data are also used for comparison. Bilinear interpolation of these gridded datasets is used to input the precipitation data at the closest grid points to the station locations. Sensitivity Analysis and Auto-calibration are performed for the SWAT model. The Nash-Sutcliffe Efficiency (NSE) and Coefficient of Determination (R2) indices are used to benchmark the model performance. Results indicate that the APHRODITE dataset performed very well on a daily scale simulation of discharge having a good NSE of 0.54 and R2 of 0.55, when compared to the discharge simulation using station data (0.68 and 0.71). The GPCP proved to be the next best dataset that was applied to the runoff modelling, with NSE and R2 of 0.46 and 0.51, respectively. The PERSIANN and TRMM rainfall data driven runoff did not show good agreement compared to the station data as both the NSE and R2 indices showed a low value of 0.3. GHCN2 and NCEP also did not show good correlations. The varied results by using these datasets indicate that although the gauge based and satellite-gauge merged products use some ground truth data, the different interpolation techniques and merging algorithms could also be a source of uncertainties. This entails a good understanding of the response of the hydrological model to different datasets and a quantification of the uncertainties in these datasets. Such a methodology is also useful for planning on Rainfall-runoff and even reservoir/river management both at rural and urban scales.

Can we improve streamflow simulation by using higher resolution rainfall information?

NASA Astrophysics Data System (ADS)

Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles

2013-04-01

The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.

Strategy for introduction of rainwater management facility considering rainfall event applied on new apartment complex

NASA Astrophysics Data System (ADS)

KIM, H.; Lee, D. K.; Yoo, S.

2014-12-01

As regional torrential rains become frequent due to climate change, urban flooding happens very often. That is why it is necessary to prepare for integrated measures against a wide range of rainfall. This study proposes introduction of effective rainwater management facilities to maximize the rainwater runoff reductions and recover natural water circulation for unpredictable extreme rainfall in apartment complex scale. The study site is new apartment complex in Hanam located in east of Seoul, Korea. It has an area of 7.28ha and is analysed using the EPA-SWMM and STORM model. First, it is analyzed that green infrastructure(GI) had efficiency of flood reduction at the various rainfall events and soil characteristics, and then the most effective value of variables are derived. In case of rainfall event, Last 10 years data of 15 minutes were used for analysis. A comparison between A(686mm rainfall during 22days) and B(661mm/4days) knew that soil infiltration of A is 17.08% and B is 5.48% of the rainfall. Reduction of runoff after introduction of the GI of A is 24.76% and B is 6.56%. These results mean that GI is effective to small rainfall intensity, and artificial rainwater retarding reservoir is needed at extreme rainfall. Second, set of target year is conducted for the recovery of hydrological cycle at the predevelopment. And an amount of infiltration, evaporation, surface runoff of the target year and now is analysed on the basis of land coverage, and an arrangement of LID facilities. Third, rainwater management scenarios are established and simulated by the SWMM-LID. Rainwater management facilities include GI(green roof, porous pavement, vegetative swale, ecological pond, and raingarden), and artificial rainwater. Design scenarios are categorized five type: 1)no GI, 2)conventional GI design(current design), 3)intensive GI design, 4)GI design+rainwater retarding reservoir 5)maximized rainwater retarding reservoir. Intensive GI design is to have attribute value to obtain the maximum efficiency for each GI facility with in-depth experts interviews. Climate change scenario is also used to set the capacity of the rainwater management facilities considering the extreme precipitation. These all scenarios are not only simulated for calculating the hydrological balance but analysed the cost for each scenarios effect.

Evaluation of rainfall simulations over West Africa in dynamically downscaled CMIP5 global circulation models

NASA Astrophysics Data System (ADS)

Akinsanola, A. A.; Ajayi, V. O.; Adejare, A. T.; Adeyeri, O. E.; Gbode, I. E.; Ogunjobi, K. O.; Nikulin, G.; Abolude, A. T.

2018-04-01

This study presents evaluation of the ability of Rossby Centre Regional Climate Model (RCA4) driven by nine global circulation models (GCMs), to skilfully reproduce the key features of rainfall climatology over West Africa for the period of 1980-2005. The seasonal climatology and annual cycle of the RCA4 simulations were assessed over three homogenous subregions of West Africa (Guinea coast, Savannah, and Sahel) and evaluated using observed precipitation data from the Global Precipitation Climatology Project (GPCP). Furthermore, the model output was evaluated using a wide range of statistical measures. The interseasonal and interannual variability of the RCA4 were further assessed over the subregions and the whole of the West Africa domain. Results indicate that the RCA4 captures the spatial and interseasonal rainfall pattern adequately but exhibits a weak performance over the Guinea coast. Findings from the interannual rainfall variability indicate that the model performance is better over the larger West Africa domain than the subregions. The largest difference across the RCA4 simulated annual rainfall was found in the Sahel. Result from the Mann-Kendall test showed no significant trend for the 1980-2005 period in annual rainfall either in GPCP observation data or in the model simulations over West Africa. In many aspects, the RCA4 simulation driven by the HadGEM2-ES perform best over the region. The use of the multimodel ensemble mean has resulted to the improved representation of rainfall characteristics over the study domain.

Using nudging to improve global-regional dynamic consistency in limited-area climate modeling: What should we nudge?

NASA Astrophysics Data System (ADS)

Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

2015-03-01

Regional climate modelling sometimes requires that the regional model be nudged towards the large-scale driving data to avoid the development of inconsistencies between them. These inconsistencies are known to produce large surface temperature and rainfall artefacts. Therefore, it is essential to maintain the synoptic circulation within the simulation domain consistent with the synoptic circulation at the domain boundaries. Nudging techniques, initially developed for data assimilation purposes, are increasingly used in regional climate modeling and offer a workaround to this issue. In this context, several questions on the "optimal" use of nudging are still open. In this study we focus on a specific question which is: What variable should we nudge? in order to maintain the consistencies between the regional model and the driving fields as much as possible. For that, a "Big Brother Experiment", where a reference atmospheric state is known, is conducted using the weather research and forecasting (WRF) model over the Euro-Mediterranean region. A set of 22 3-month simulations is performed with different sets of nudged variables and nudging options (no nudging, indiscriminate nudging, spectral nudging) for summer and winter. The results show that nudging clearly improves the model capacity to reproduce the reference fields. However the skill scores depend on the set of variables used to nudge the regional climate simulations. Nudging the tropospheric horizontal wind is by far the key variable to nudge to simulate correctly surface temperature and wind, and rainfall. To a lesser extent, nudging tropospheric temperature also contributes to significantly improve the simulations. Indeed, nudging tropospheric wind or temperature directly impacts the simulation of the tropospheric geopotential height and thus the synoptic scale atmospheric circulation. Nudging moisture improves the precipitation but the impact on the other fields (wind and temperature) is not significant. As an immediate consequence, nudging tropospheric wind, temperature and moisture in WRF gives by far the best results with respect to the Big-Brother simulation. However, we noticed that a residual bias of the geopotential height persists due to a negative surface pressure anomaly which suggests that surface pressure is the missing quantity to nudge. Nudging the geopotential has no discernible effect. Finally, it should be noted that the proposed strategy ensures a dynamical consistency between the driving field and the simulated small-scale field but it does not ensure the best "observed" fine scale field because of the possible impact of incorrect driving large-scale field.

Simulation of precipitation by weather pattern and frontal analysis

NASA Astrophysics Data System (ADS)

Wilby, Robert

1995-12-01

Daily rainfall from two sites in central and southern England was stratified according to the presence or absence of weather fronts and then cross-tabulated with the prevailing Lamb Weather Type (LWT). A semi-Markov chain model was developed for simulating daily sequences of LWTs from matrices of transition probabilities between weather types for the British Isles 1970-1990. Daily and annual rainfall distributions were then simulated from the prevailing LWTs using historic conditional probabilities for precipitation occurrence and frontal frequencies. When compared with a conventional rainfall generator the frontal model produced improved estimates of the overall size distribution of daily rainfall amounts and in particular the incidence of low-frequency high-magnitude totals. Further research is required to establish the contribution of individual frontal sub-classes to daily rainfall totals and of long-term fluctuations in frontal frequencies to conditional probabilities.

Development and validation of a runoff and erosion model for lowland drained catchments

NASA Astrophysics Data System (ADS)

Grangeon, Thomas; Cerdan, Olivier; Vandromme, Rosalie; Landemaine, Valentin; Manière, Louis; Salvador-Blanes, Sébastien; Foucher, Anthony; Evrard, Olivier

2017-04-01

Modelling water and sediment transfer in lowland catchments is complex as both hortonian and saturation excess-flow occur in these environments. Moreover, their dynamics was complexified by the installation of tile drainage networks or stream redesign. To the best of our knowledge, few models are able to simulate saturation runoff as well as hortonian runoff in tile-drained catchments. Most of the time, they are used for small scale applications due to their high degree of complexity. In this context, a model of intermediate complexity was developed to simulate the hydrological and erosion processes at the catchment scale in lowland environments. This GIS-based, spatially distributed and lumped model at the event scale uses a theoretical hydrograph to approximate within-event temporal variations. It comprises two layers used to represent surface and subsurface transfers. Observations of soil surface characteristics (i.e. vegetation density, soil crusting and roughness) were used to document spatial variations of physical soil characteristics (e.g. infiltration capacity). Flow was routed depending on the local slope, using LIDAR elevation data. Both the diffuse and the gully erosion are explicitly described. The model ability to simulate water and sediment dynamics at the catchment scale was evaluated using the monitoring of a selection of flood events in a small, extensively cultivated catchment (the Louroux catchment, Loire River basin, central France; 25 km2). In this catchment, five monitoring stations were equipped with water level sensors, turbidity probes, and automatic samplers. Discharge and suspended sediment concentration were deduced from field measurements. One station was installed at the outlet of a tile drain and was used to parameterize fluxes supplied by the drainage network. The selected floods were representative of various rainfall and soil surface conditions (e.g. low-intensity rainfall occurring on saturated soils as well as intense rainfall occurring on dry soils in spring). The model was able to reproduce the runoff volumes for these different situations, and performed well, especially in winter (the relationship between observed and modeled values has R2=0.72) when most of the sediment are transferred. Therefore, future work will evaluate the model ability to reproduce the erosion and sediment dynamics in this catchment in order to provide a tool for sediment management in these lowland environments draining agricultural land where river siltation is problematic.

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

NASA Astrophysics Data System (ADS)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different 'homogeneous monsoon regions'.

Extreme Precipitation and High-Impact Landslides

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Huffman, George; Peters-Lidard, Christa

2012-01-01

It is well known that extreme or prolonged rainfall is the dominant trigger of landslides; however, there remain large uncertainties in characterizing the distribution of these hazards and meteorological triggers at the global scale. Researchers have evaluated the spatiotemporal distribution of extreme rainfall and landslides at local and regional scale primarily using in situ data, yet few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This research uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from Tropical Rainfall Measuring Mission (TRMM) data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurence of precipitation and rainfall-triggered landslides globally. The GLC, available from 2007 to the present, contains information on reported rainfall-triggered landslide events around the world using online media reports, disaster databases, etc. When evaluating this database, we observed that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This research also considers the sources for this extreme rainfall, citing teleconnections from ENSO as likely contributors to regional precipitation variability. This work demonstrates the potential for using satellite-based precipitation estimates to identify potentially active landslide areas at the global scale in order to improve landslide cataloging and quantify landslide triggering at daily, monthly and yearly time scales.

Comparison of different synthetic 5-min rainfall time series on the results of rainfall runoff simulations in urban drainage modelling

NASA Astrophysics Data System (ADS)

Krämer, Stefan; Rohde, Sophia; Schröder, Kai; Belli, Aslan; Maßmann, Stefanie; Schönfeld, Martin; Henkel, Erik; Fuchs, Lothar

2015-04-01

The design of urban drainage systems with numerical simulation models requires long, continuous rainfall time series with high temporal resolution. However, suitable observed time series are rare. As a result, usual design concepts often use uncertain or unsuitable rainfall data, which renders them uneconomic or unsustainable. An expedient alternative to observed data is the use of long, synthetic rainfall time series as input for the simulation models. Within the project SYNOPSE, several different methods to generate synthetic rainfall data as input for urban drainage modelling are advanced, tested, and compared. Synthetic rainfall time series of three different precipitation model approaches, - one parametric stochastic model (alternating renewal approach), one non-parametric stochastic model (resampling approach), one downscaling approach from a regional climate model-, are provided for three catchments with different sewer system characteristics in different climate regions in Germany: - Hamburg (northern Germany): maritime climate, mean annual rainfall: 770 mm; combined sewer system length: 1.729 km (City center of Hamburg), storm water sewer system length (Hamburg Harburg): 168 km - Brunswick (Lower Saxony, northern Germany): transitional climate from maritime to continental, mean annual rainfall: 618 mm; sewer system length: 278 km, connected impervious area: 379 ha, height difference: 27 m - Friburg in Brisgau (southern Germany): Central European transitional climate, mean annual rainfall: 908 mm; sewer system length: 794 km, connected impervious area: 1 546 ha, height difference 284 m Hydrodynamic models are set up for each catchment to simulate rainfall runoff processes in the sewer systems. Long term event time series are extracted from the - three different synthetic rainfall time series (comprising up to 600 years continuous rainfall) provided for each catchment and - observed gauge rainfall (reference rainfall) according national hydraulic design standards. The synthetic and reference long term event time series are used as rainfall input for the hydrodynamic sewer models. For comparison of the synthetic rainfall time series against the reference rainfall and against each other the number of - surcharged manholes, - surcharges per manhole, - and the average surcharge volume per manhole are applied as hydraulic performance criteria. The results are discussed and assessed to answer the following questions: - Are the synthetic rainfall approaches suitable to generate high resolution rainfall series and do they produce, - in combination with numerical rainfall runoff models - valid results for design of urban drainage systems? - What are the bounds of uncertainty in the runoff results depending on the synthetic rainfall model and on the climate region? The work is carried out within the SYNOPSE project, funded by the German Federal Ministry of Education and Research (BMBF).

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

Using integrated modeling for generating watershed-scale dynamic flood maps for Hurricane Harvey

NASA Astrophysics Data System (ADS)

Saksena, S.; Dey, S.; Merwade, V.; Singhofen, P. J.

2017-12-01

Hurricane Harvey, which was categorized as a 1000-year return period event, produced unprecedented rainfall and flooding in Houston. Although the expected rainfall was forecasted much before the event, there was no way to identify which regions were at higher risk of flooding, the magnitude of flooding, and when the impacts of rainfall would be highest. The inability to predict the location, duration, and depth of flooding created uncertainty over evacuation planning and preparation. This catastrophic event highlighted that the conventional approach to managing flood risk using 100-year static flood inundation maps is inadequate because of its inability to predict flood duration and extents for 500-year or 1000-year return period events in real-time. The purpose of this study is to create models that can dynamically predict the impacts of rainfall and subsequent flooding, so that necessary evacuation and rescue efforts can be planned in advance. This study uses a 2D integrated surface water-groundwater model called ICPR (Interconnected Channel and Pond Routing) to simulate both the hydrology and hydrodynamics for Hurricane Harvey. The methodology involves using the NHD stream network to create a 2D model that incorporates rainfall, land use, vadose zone properties and topography to estimate streamflow and generate dynamic flood depths and extents. The results show that dynamic flood mapping captures the flood hydrodynamics more accurately and is able to predict the magnitude, extent and time of occurrence for extreme events such as Hurricane Harvey. Therefore, integrated modeling has the potential to identify regions that are more susceptible to flooding, which is especially useful for large-scale planning and allocation of resources for protection against future flood risk.

Influence of net freshwater supply on salinity in Florida Bay

USGS Publications Warehouse

Nuttle, William K.; Fourqurean, James W.; Cosby, Bernard J.; Zieman, Joseph C.; Robblee, Michael B.

2000-01-01

An annual water budget for Florida Bay, the large, seasonally hypersaline estuary in the Everglades National Park, was constructed using physically based models and long‐term (31 years) data on salinity, hydrology, and climate. Effects of seasonal and interannual variations of the net freshwater supply (runoff plus rainfall minus evaporation) on salinity variation within the bay were also examined. Particular attention was paid to the effects of runoff, which are the focus of ambitious plans to restore and conserve the Florida Bay ecosystem. From 1965 to 1995 the annual runoff from the Everglades into the bay was less than one tenth of the annual direct rainfall onto the bay, while estimated annual evaporation slightly exceeded annual rainfall. The average net freshwater supply to the bay over a year was thus approximately zero, and interannual variations in salinity appeared to be affected primarily by interannual fluctuations in rainfall. At the annual scale, runoff apparently had little effect on the bay as a whole during this period. On a seasonal basis, variations in rainfall, evaporation, and runoff were not in phase, and the net freshwater supply to the bay varied between positive and negative values, contributing to a strong seasonal pattern in salinity, especially in regions of the bay relatively isolated from exchanges with the Gulf of Mexico and Atlantic Ocean. Changes in runoff could have a greater effect on salinity in the bay if the seasonal patterns of rainfall and evaporation and the timing of the runoff are considered. One model was also used to simulate spatial and temporal patterns of salinity responses expected to result from changes in net freshwater supply. Simulations in which runoff was increased by a factor of 2 (but with no change in spatial pattern) indicated that increased runoff will lower salinity values in eastern Florida Bay, increase the variability of salinity in the South Region, but have little effect on salinity in the Central and West Regions.

A New Look at Rainfall Fluctuations and Scaling Properties of Spatial Rainfall Using Orthogonal Wavelets.

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1993-02-01

It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

A new look at rainfall fluctuations and scaling properties of spatial rainfall using orthogonal wavelets

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1993-01-01

It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

Influence of climate variability versus change at multi-decadal time scales on hydrological extremes

NASA Astrophysics Data System (ADS)

Willems, Patrick

2014-05-01

Recent studies have shown that rainfall and hydrological extremes do not randomly occur in time, but are subject to multidecadal oscillations. In addition to these oscillations, there are temporal trends due to climate change. Design statistics, such as intensity-duration-frequency (IDF) for extreme rainfall or flow-duration-frequency (QDF) relationships, are affected by both types of temporal changes (short term and long term). This presentation discusses these changes, how they influence water engineering design and decision making, and how this influence can be assessed and taken into account in practice. The multidecadal oscillations in rainfall and hydrological extremes were studied based on a technique for the identification and analysis of changes in extreme quantiles. The statistical significance of the oscillations was evaluated by means of a non-parametric bootstrapping method. Oscillations in large scale atmospheric circulation were identified as the main drivers for the temporal oscillations in rainfall and hydrological extremes. They also explain why spatial phase shifts (e.g. north-south variations in Europe) exist between the oscillation highs and lows. Next to the multidecadal climate oscillations, several stations show trends during the most recent decades, which may be attributed to climate change as a result of anthropogenic global warming. Such attribution to anthropogenic global warming is, however, uncertain. It can be done based on simulation results with climate models, but it is shown that the climate model results are too uncertain to enable a clear attribution. Water engineering design statistics, such as extreme rainfall IDF or peak or low flow QDF statistics, obviously are influenced by these temporal variations (oscillations, trends). It is shown in the paper, based on the Brussels 10-minutes rainfall data, that rainfall design values may be about 20% biased or different when based on short rainfall series of 10 to 15 years length, and still 8% for series of 25 years lengths. Methods for bias correction are demonstrated. The definition of "bias" depends on a number of factors, which needs further debate in the hydrological and water engineering community. References: Willems P. (2013), 'Multidecadal oscillatory behaviour of rainfall extremes in Europe', Climatic Change, 120(4), 931-944 Willems, P. (2013). 'Adjustment of extreme rainfall statistics accounting for multidecadal climate oscillations', Journal of Hydrology, 490, 126-133 Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012), 'Impacts of climate change on rainfall extremes and urban drainage', IWA Publishing, 252p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

Modulation of Heavy Rainfall in the Middle East and North Africa by Madden-Julian Oscillation Using High Resolution Atmospheric General Circulation Model

NASA Astrophysics Data System (ADS)

Deng, L.; Stenchikov, G. L.; McCabe, M. F.; Bangalath, H. K.

2014-12-01

Recently, the modulation of subtropical rainfall by the dominant tropical intraseasonal signal of the Madden-Julian Oscillation (MJO), has been explored through the discussion of the MJO-convection-induced Kelvin and Rossby wave related teleconnection patterns. Our study focuses on characterizing the modulation of heavy rainfall in the Middle East and North Africa (MENA) region by the MJO, using the Geophysical Fluid Dynamics Laboratory (GFDL) global High Resolution Atmospheric Model (HIRAM) simulations (25-km; 1979-2012) and a combination of available atmospheric products from satellite, in-situ and reanalysis data. The observed Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) and the simulated SST from GFDL's global coupled carbon-climate Earth System Models (ESM2M) are employed in HIRAM to investigate the sensitivity of the simulated heavy rainfall and MJO to SST. The future trend of the extreme rainfalls and their links to the MJO response to climate change are examined using HIRAM simulations of 2012-2050 with the RCP4.5 and RCP 8.5 scenarios to advance the possibility of characterization and forecasting of future extreme rainfall events in the MENA region.

WRF simulation of a severe hailstorm over Baramati: a study into the space-time evolution

NASA Astrophysics Data System (ADS)

Murthy, B. S.; Latha, R.; Madhuparna, H.

2018-04-01

Space-time evolution of a severe hailstorm occurred over the western India as revealed by WRF-ARW simulations are presented. We simulated a specific event centered over Baramati (18.15°N, 74.58°E, 537 m AMSL) on March 9, 2014. A physical mechanism, proposed as a conceptual model, signifies the role of multiple convective cells organizing through outflows leading to a cold frontal type flow, in the presence of a low over the northern Arabian Sea, propagates from NW to SE triggering deep convection and precipitation. A `U' shaped cold pool encircled by a converging boundary forms to the north of Baramati due to precipitation behind the moisture convergence line with strong updrafts ( 15 ms-1) leading to convective clouds extending up to 8 km in a narrow region of 30 km. The outflows from the convective clouds merge with the opposing southerly or southwesterly winds from the Arabian Sea and southerly or southeasterly winds from the Bay of Bengal resulting in moisture convergence (maximum 80 × 10-3 g kg-1 s-1). The vertical profile of the area-averaged moisture convergence over the cold pool shows strong convergence above 850 hPa and divergence near the surface indicating elevated convection. Radar reflectivity (50-60 dBZ) and vertical component of vorticity maximum ( 0.01-0.14 s-1) are observed along the convergence zone. Stratiform clouds ahead of the squall line and parallel wind flow at 850 hPa and nearly perpendicular flow at higher levels relative to squall line as evidenced by relatively low and wide-spread reflectivity suggests that organizational mode of squall line may be categorized as `Mixed Mode' type where northern part can be a parallel stratiform while the southern part resembles with a leading stratiform. Simulated rainfall (grid scale 27 km) leads the observed rainfall by 1 h while its magnitude is 2 times of the observed rainfall (grid scale 100 km) derived from Kalpana-1. Thus, this study indicates that under synoptically favorable conditions, WRF-ARW could simulate thunderstorm evolution reasonably well although there is some space-time error which might, perhaps, be the reason for lower CAPE (observed by upper air sounding) on the simulation day.

Impact of large-scale circulation changes in the North Atlantic sector on the current and future Mediterranean winter hydroclimate

NASA Astrophysics Data System (ADS)

Barcikowska, Monika J.; Kapnick, Sarah B.; Feser, Frauke

2018-03-01

The Mediterranean region, located in the transition zone between the dry subtropical and wet European mid-latitude climate, is very sensitive to changes in the global mean climate state. Projecting future changes of the Mediterranean hydroclimate under global warming therefore requires dynamic climate models to reproduce the main mechanisms controlling regional hydroclimate with sufficiently high resolution to realistically simulate climate extremes. To assess future winter precipitation changes in the Mediterranean region we use the Geophysical Fluid Dynamics Laboratory high-resolution general circulation model for control simulations with pre-industrial greenhouse gas and aerosol concentrations which are compared to future scenario simulations. Here we show that the coupled model is able to reliably simulate the large-scale winter circulation, including the North Atlantic Oscillation and Eastern Atlantic patterns of variability, and its associated impacts on the mean Mediterranean hydroclimate. The model also realistically reproduces the regional features of daily heavy rainfall, which are absent in lower-resolution simulations. A five-member future projection ensemble, which assumes comparatively high greenhouse gas emissions (RCP8.5) until 2100, indicates a strong winter decline in Mediterranean precipitation for the coming decades. Consistent with dynamical and thermodynamical consequences of a warming atmosphere, derived changes feature a distinct bipolar behavior, i.e. wetting in the north—and drying in the south. Changes are most pronounced over the northwest African coast, where the projected winter precipitation decline reaches 40% of present values. Despite a decrease in mean precipitation, heavy rainfall indices show drastic increases across most of the Mediterranean, except the North African coast, which is under the strong influence of the cold Canary Current.

Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations

NASA Technical Reports Server (NTRS)

Iguchi, Takamichi; Tao, Wei-Kuo; Wu, Di; Peters-Lidard, Christa; Santanello, Joseph A.; Kemp, Eric; Tian, Yudong; Case, Jonathan; Wang, Weile; Ferraro, Robert;

Impact of Assimilation on Heavy Rainfall Simulations Using WRF Model: Sensitivity of Assimilation Results to Background Error Statistics

NASA Astrophysics Data System (ADS)

Rakesh, V.; Kantharao, B.

2017-03-01

Data assimilation is considered as one of the effective tools for improving forecast skill of mesoscale models. However, for optimum utilization and effective assimilation of observations, many factors need to be taken into account while designing data assimilation methodology. One of the critical components that determines the amount and propagation observation information into the analysis, is model background error statistics (BES). The objective of this study is to quantify how BES in data assimilation impacts on simulation of heavy rainfall events over a southern state in India, Karnataka. Simulations of 40 heavy rainfall events were carried out using Weather Research and Forecasting Model with and without data assimilation. The assimilation experiments were conducted using global and regional BES while the experiment with no assimilation was used as the baseline for assessing the impact of data assimilation. The simulated rainfall is verified against high-resolution rain-gage observations over Karnataka. Statistical evaluation using several accuracy and skill measures shows that data assimilation has improved the heavy rainfall simulation. Our results showed that the experiment using regional BES outperformed the one which used global BES. Critical thermo-dynamic variables conducive for heavy rainfall like convective available potential energy simulated using regional BES is more realistic compared to global BES. It is pointed out that these results have important practical implications in design of forecast platforms while decision-making during extreme weather events

Comparing a simple methodology to evaluate hydrodynamic parameters with rainfall simulation experiments

NASA Astrophysics Data System (ADS)

Di Prima, Simone; Bagarello, Vincenzo; Bautista, Inmaculada; Burguet, Maria; Cerdà, Artemi; Iovino, Massimo; Prosdocimi, Massimo

2016-04-01

Studying soil hydraulic properties is necessary for interpreting and simulating many hydrological processes having environmental and economic importance, such as rainfall partition into infiltration and runoff. The saturated hydraulic conductivity, Ks, exerts a dominating influence on the partitioning of rainfall in vertical and lateral flow paths. Therefore, estimates of Ks are essential for describing and modeling hydrological processes (Zimmermann et al., 2013). According to several investigations, Ks data collected by ponded infiltration tests could be expected to be unusable for interpreting field hydrological processes, and particularly infiltration. In fact, infiltration measured by ponding give us information about the soil maximum or potential infiltration rate (Cerdà, 1996). Moreover, especially for the hydrodynamic parameters, many replicated measurements have to be carried out to characterize an area of interest since they are known to vary widely both in space and time (Logsdon and Jaynes, 1996; Prieksat et al., 1994). Therefore, the technique to be applied at the near point scale should be simple and rapid. Bagarello et al. (2014) and Alagna et al. (2015) suggested that the Ks values determined by an infiltration experiment carried applying water at a relatively large distance from the soil surface could be more appropriate than those obtained with a low height of water pouring to explain surface runoff generation phenomena during intense rainfall events. These authors used the Beerkan Estimation of Soil Transfer parameters (BEST) procedure for complete soil hydraulic characterization (Lassabatère et al., 2006) to analyze the field infiltration experiment. This methodology, combining low and high height of water pouring, seems appropriate to test the effect of intense and prolonged rainfall events on the hydraulic characteristics of the surface soil layer. In fact, an intense and prolonged rainfall event has a perturbing effect on the soil surface and, reasonably, it can better be represented by the high runs than the low runs (Alagna et al., 2015). Obviously, this methodology is also simpler than an approach involving soil characterization both before and after natural or simulated rainfall since it needs less equipment and field work. On the other hand, rainfall simulation experiments are more realistic and accurate, but also more sophisticated and costly (Cerdà, 1997). Rainfall simulation is often used to measure the infiltration process (e.g., Bhardwaj and Singh, 1992; Cerdà, 1999, 1997, 1996; Cerdà and Doerr, 2007; Iserloh et al., 2013; Liu et al., 2011; Tricker, 1979), and it has become an important method for assessing the subjects of soil erosion and soil hydrological processes (Iserloh et al., 2013). Its application allows a quick, specific and reproducible assessment of the meaning and impact of several factors, such as slope, soil type (infiltration, permeability), soil moisture, splash effect of raindrops (aggregate stability), surface structure, vegetation cover and vegetation structure (Bowyer-Bower and Burt, 1989). The objectives of this investigation are: (i) to compare infiltration rates measured by applying water at a relatively large distance from the soil surface with those obtained by rainfall simulation experiments and (ii) to verify if the Ks values determined with the BEST procedure are in line with the occurrence of runoff measured with a more robust methodology. Acknowledgements The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 603498 (RECARE project). References Alagna, V., Bagarello, V., Di Prima, S., Giordano, G., Iovino, M., 2015. Testing infiltration run effects on the estimated hydrodynamic parameters of a sandy-loam soil. Submitted to Geoderma. Bagarello, V., Castellini, M., Di Prima, S., Iovino, M., 2014. Soil hydraulic properties determined by infiltration experiments and different heights of water pouring. Geoderma 213, 492-501. doi:10.1016/j.geoderma.2013.08.032 Bhardwaj, A., Singh, R., 1992. Development of a portable rainfall simulator infiltrometer for infiltration, runoff and erosion studies. Agricultural Water Management 22, 235-248. doi:10.1016/0378-3774(92)90028-U Bouwer, H., 1966. Rapid field measurement of air entry value and hydraulic conductivity of soil as significant parameters in flow system analysis. Water Resour. Res. 2, 729-738. doi:10.1029/WR002i004p00729 Bowyer-Bower, T.A.S., Burt, T.P., 1989. Rainfall simulators for investigating soil response to rainfall. Soil Technology 2, 1-16. doi:10.1016/S0933-3630(89)80002-9 Cerdà, A., 1999. Simuladores de lluvia y su aplicación a la Geomorfologia: estado de la cuestión. Cuadernos de investigación geográfica 45-84. Cerdà, A., 1997. Seasonal changes of the infiltration rates in a Mediterranean scrubland on limestone. Journal of Hydrology 198, 209-225. doi:10.1016/S0022-1694(96)03295-7 Cerdà, A., 1996. Seasonal variability of infiltration rates under contrasting slope conditions in southeast Spain. Geoderma 69, 217-232. doi:10.1016/0016-7061(95)00062-3 Cerdà, A., Doerr, S.H., 2007. Soil wettability, runoff and erodibility of major dry-Mediterranean land use types on calcareous soils. Hydrol. Process. 21, 2325-2336. doi:10.1002/hyp.6755 Iserloh, T., Ries, J.B., Arnáez, J., Boix-Fayos, C., Butzen, V., Cerdà, A., Echeverría, M.T., Fernández-Gálvez, J., Fister, W., Geißler, C., Gómez, J.A., Gómez-Macpherson, H., Kuhn, N.J., Lázaro, R., León, F.J., Martínez-Mena, M., Martínez-Murillo, J.F., Marzen, M., Mingorance, M.D., Ortigosa, L., Peters, P., Regüés, D., Ruiz-Sinoga, J.D., Scholten, T., Seeger, M., Solé-Benet, A., Wengel, R., Wirtz, S., 2013. European small portable rainfall simulators: A comparison of rainfall characteristics. CATENA 110, 100-112. doi:10.1016/j.catena.2013.05.013 Lassabatère, L., Angulo-Jaramillo, R., Soria Ugalde, J.M., Cuenca, R., Braud, I., Haverkamp, R., 2006. Beerkan Estimation of Soil Transfer Parameters through Infiltration Experiments - BEST. Soil Science Society of America Journal 70, 521. doi:10.2136/sssaj2005.0026 Liu, H., Lei, T.W., Zhao, J., Yuan, C.P., Fan, Y.T., Qu, L.Q., 2011. Effects of rainfall intensity and antecedent soil water content on soil infiltrability under rainfall conditions using the run off-on-out method. Journal of Hydrology 396, 24-32. doi:10.1016/j.jhydrol.2010.10.028 Logsdon, S.D., Jaynes, D.B., 1996. Spatial Variability of Hydraulic Conductivity in a Cultivated Field at Different Times. Soil Science Society of America Journal 60, 703. doi:10.2136/sssaj1996.03615995006000030003x Prieksat, M.A., Kaspar, T.C., Ankeny, M.D., 1994. Positional and Temporal Changes in Ponded Infiltration in a Corn Field. Soil Science Society of America Journal 58, 181. doi:10.2136/sssaj1994.03615995005800010026x Tricker, A.S., 1979. The design of a portable rainfall simulator infiltrometer. Journal of Hydrology 41, 143-147. doi:10.1016/0022-1694(79)90111-2 van De Giesen, N.C., Stomph, T.J., de Ridder, N., 2000. Scale effects of Hortonian overland flow and rainfall-runoff dynamics in a West African catena landscape. Hydrol. Process. 14, 165-175. doi:10.1002/(SICI)1099-1085(200001)14:1<165::AID-HYP920>3.0.CO;2-1 Zimmermann, A., Schinn, D.S., Francke, T., Elsenbeer, H., Zimmermann, B., 2013. Uncovering patterns of near-surface saturated hydraulic conductivity in an overland flow-controlled landscape. Geoderma 195-196, 1-11. doi:10.1016/j.geoderma.2012.11.002

Evidence of equilibrium peak runoff rates in steep tropical terrain on the island of Dominica during Tropical Storm Erika, August 27, 2015

NASA Astrophysics Data System (ADS)

Ogden, Fred L.

2016-11-01

Tropical Storm Erika was a weakly organized tropical storm when its center of circulation passed more than 150 km north of the island of Dominica on August 27, 2015. Hurricane hunter flights had difficulty finding the center of circulation as the storm encountered a high shear environment. Satellite and radar observations showed gyres imbedded within the broader circulation. Radar observations from Guadeloupe show that one of these gyres formed in convergent mid-level flow triggered by orographic convection over the island of Dominica. Gauge-adjusted radar rainfall data indicated between 300 and 750 mm of rainfall on Dominica, most of it over a four hour period. The result was widespread flooding, destruction of property, and loss of life. The extremity of the rainfall on steep watersheds covered with shallow soils was hypothesized to result in near-equilibrium runoff conditions where peak runoff rates equal the watershed-average peak rainfall rate minus a small constant loss rate. Rain gauge adjusted radar rainfall estimates and indirect peak discharge (IPD) measurements from 16 rivers at watershed areas ranging from 0.9 to 31.4 km2 using the USGS Slope-Area method allowed testing of this hypothesis. IPD measurements were compared against the global envelope of maximum observed flood peaks versus drainage area and against simulations using the U.S. Army Corps of Engineers Gridded Surface/Subsurface Hydrologic Analysis (GSSHA) model to detect landslide-affected peak flows. Model parameter values were estimated from the literature. Reasonable agreement was found between GSSHA simulated peak flows and IPD measurements in some watersheds. Results showed that landslide dam failure affected peak flows in 5 of the 16 rivers, with peak flows significantly greater than the envelope curve values for the flood of record for like-sized watersheds on the planet. GSSHA simulated peak discharges showed that the remaining 11 peak flow values were plausible. Simulations of an additional 24 watersheds ranging in size from 2.2 to 75.4 km2 provided confirmation that the IPD measurements varied from 40 to nearly 100% of the envelope curve value depending on storm-total rainfall. Results presented in this paper support the hypothesis that on average, the peak discharges scaled linearly with drainage area, and the constant of proportionality was equivalent to 134 mm h-1, or a unit discharge of 37.22 m3 s-1 km-2. The results also indicate that after the available watershed storage was filled after approximately 450-500 mm of rain fell, runoff efficiencies exceeded 50-60%, and peak runoff rates were more than 80% of the peak rainfall rate minus a small constant loss rate of 20 mm h-1. These findings have important implications for design of resilient infrastructure, and means that rainfall rate was the primary determinant of peak flows once the available storage was filled in the absences of landslide dam failure.

The role of stochastic storms on hillslope runoff generation and connectivity in a dryland basin

NASA Astrophysics Data System (ADS)

Michaelides, K.; Singer, M. B.; Mudd, S. M.

2016-12-01

Despite low annual rainfall, dryland basins can generate significant surface runoff during certain rainstorms, which can cause flash flooding and high rates of erosion. However, it remains challenging to anticipate the nature and frequency of runoff generation in hydrological systems which are driven by spatially and temporally stochastic rainstorms. In particular, the stochasticity of rainfall presents challenges to simulating the hydrological response of dryland basins and understanding flow connectivity from hillslopes to the channel. Here we simulate hillslope runoff generation using rainfall characteristics produced by a simple stochastic rainfall generator, which is based on a rich rainfall dataset from the Walnut Gulch Experimental Watershed (WGEW) in Arizona, USA. We assess hillslope runoff generation using the hydrological model, COUP2D, driven by a subset of characteristic output from multiple ensembles of decadal monsoonal rainfall from the stochastic rainfall generator. The rainfall generator operates across WGEW by simulating storms with areas smaller than the basin and enables explicit characterization of rainfall characteristics at any location. We combine the characteristics of rainfall intensity and duration with data on rainstorm area and location to model the surface runoff properties (depth, velocity, duration, distance downslope) on a range of hillslopes within the basin derived from LiDAR analysis. We also analyze connectivity of flow from hillslopes to the channel for various combinations of hillslopes and storms. This approach provides a framework for understanding spatial and temporal dynamics of runoff generation and connectivity that is faithful to the hydrological characteristics of dryland environments.

A study on large-scale nudging effects in regional climate model simulation

NASA Astrophysics Data System (ADS)

Yhang, Yoo-Bin; Hong, Song-You

2011-05-01

The large-scale nudging effects on the East Asian summer monsoon (EASM) are examined using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM). The NCEP/DOE reanalysis data is used to provide large-scale forcings for RSM simulations, configured with an approximately 50-km grid over East Asia, centered on the Korean peninsula. The RSM with a variant of spectral nudging, that is, the scale selective bias correction (SSBC), is forced by perfect boundary conditions during the summers (June-July-August) from 1979 to 2004. The two summers of 2000 and 2004 are investigated to demonstrate the impact of SSBC on precipitation in detail. It is found that the effect of SSBC on the simulated seasonal precipitation is in general neutral without a discernible advantage. Although errors in large-scale circulation for both 2000 and 2004 are reduced by using the SSBC method, the impact on simulated precipitation is found to be negative in 2000 and positive in 2004 summers. One possible reason for a different effect is that precipitation in the summer of 2004 is characterized by a strong baroclinicity, while precipitation in 2000 is caused by thermodynamic instability. The reduction of convective rainfall over the oceans by the application of the SSBC method seems to play an important role in modeled atmosphere.

Stochastic generation of hourly rainstorm events in Johor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nojumuddin, Nur Syereena; Yusof, Fadhilah; Yusop, Zulkifli

2015-02-03

Engineers and researchers in water-related studies are often faced with the problem of having insufficient and long rainfall record. Practical and effective methods must be developed to generate unavailable data from limited available data. Therefore, this paper presents a Monte-Carlo based stochastic hourly rainfall generation model to complement the unavailable data. The Monte Carlo simulation used in this study is based on the best fit of storm characteristics. Hence, by using the Maximum Likelihood Estimation (MLE) and Anderson Darling goodness-of-fit test, lognormal appeared to be the best rainfall distribution. Therefore, the Monte Carlo simulation based on lognormal distribution was usedmore » in the study. The proposed model was verified by comparing the statistical moments of rainstorm characteristics from the combination of the observed rainstorm events under 10 years and simulated rainstorm events under 30 years of rainfall records with those under the entire 40 years of observed rainfall data based on the hourly rainfall data at the station J1 in Johor over the period of 1972–2011. The absolute percentage error of the duration-depth, duration-inter-event time and depth-inter-event time will be used as the accuracy test. The results showed the first four product-moments of the observed rainstorm characteristics were close with the simulated rainstorm characteristics. The proposed model can be used as a basis to derive rainfall intensity-duration frequency in Johor.« less

A spatio-temporal evaluation of the WRF physical parameterisations for numerical rainfall simulation in semi-humid and semi-arid catchments of Northern China

NASA Astrophysics Data System (ADS)

Tian, Jiyang; Liu, Jia; Wang, Jianhua; Li, Chuanzhe; Yu, Fuliang; Chu, Zhigang

2017-07-01

Mesoscale Numerical Weather Prediction systems can provide rainfall products at high resolutions in space and time, playing an increasingly more important role in water management and flood forecasting. The Weather Research and Forecasting (WRF) model is one of the most popular mesoscale systems and has been extensively used in research and practice. However, for hydrologists, an unsolved question must be addressed before each model application in a different target area. That is, how are the most appropriate combinations of physical parameterisations from the vast WRF library selected to provide the best downscaled rainfall? In this study, the WRF model was applied with 12 designed parameterisation schemes with different combinations of physical parameterisations, including microphysics, radiation, planetary boundary layer (PBL), land-surface model (LSM) and cumulus parameterisations. The selected study areas are two semi-humid and semi-arid catchments located in the Daqinghe River basin, Northern China. The performance of WRF with different parameterisation schemes is tested for simulating eight typical 24-h storm events with different evenness in space and time. In addition to the cumulative rainfall amount, the spatial and temporal patterns of the simulated rainfall are evaluated based on a two-dimensional composed verification statistic. Among the 12 parameterisation schemes, Scheme 4 outperforms the other schemes with the best average performance in simulating rainfall totals and temporal patterns; in contrast, Scheme 6 is generally a good choice for simulations of spatial rainfall distributions. Regarding the individual parameterisations, Single-Moment 6 (WSM6), Yonsei University (YSU), Kain-Fritsch (KF) and Grell-Devenyi (GD) are better choices for microphysics, planetary boundary layers (PBL) and cumulus parameterisations, respectively, in the study area. These findings provide helpful information for WRF rainfall downscaling in semi-humid and semi-arid areas. The methodologies to design and test the combination schemes of parameterisations can also be regarded as a reference for generating ensembles in numerical rainfall predictions using the WRF model.

Intra-Seasonal Rainfall Variations and Linkage with Kharif Crop Production: An Attempt to Evaluate Predictability of Sub-Seasonal Rainfall Events

NASA Astrophysics Data System (ADS)

Singh, Ankita; Ghosh, Kripan; Mohanty, U. C.

2018-03-01

The sub-seasonal variation of Indian summer monsoon rainfall highly impacts Kharif crop production in comparison with seasonal total rainfall. The rainfall frequency and intensity corresponding to various rainfall events are found to be highly related to crop production and therefore, the predictability of such events are considered to be diagnosed. Daily rainfall predictions are made available by one of the coupled dynamical model National Centers for Environmental Prediction Climate Forecast System (NCEPCFS). A large error in the simulation of daily rainfall sequence influences to take up a bias correction and for that reason, two approaches are used. The bias-corrected GCM is able to capture the inter-annual variability in rainfall events. Maximum prediction skill of frequency of less rainfall (LR) event is observed during the month of September and a similar result is also noticed for moderate rainfall event with maximum skill over the central parts of the country. On the other hand, the impact of rainfall weekly rainfall intensity is evaluated against the Kharif rice production. It is found that weekly rainfall intensity during July is having a significant impact on Kharif rice production, but the corresponding skill was found very low in GCM. The GCM are able to simulate the less and moderate rainfall frequency with significant skill.

The evolution of sub-monsoon systems in the Afro-Asian monsoon region during the Holocene - comparison of different transient climate model simulations

NASA Astrophysics Data System (ADS)

Dallmeyer, A.; Claussen, M.; Fischer, N.; Haberkorn, K.; Wagner, S.; Pfeiffer, M.; Jin, L.; Khon, V.; Wang, Y.; Herzschuh, U.

2014-05-01

The recently proposed global monsoon hypothesis interprets monsoon systems as part of one global-scale atmospheric overturning circulation, implying a connection between the regional monsoon systems and an in-phase behaviour of all northern hemispheric monsoons on annual timescales (Trenberth et al., 2000). Whether this concept can be applied to past climates and variability on longer timescales is still under debate, because the monsoon systems exhibit different regional characteristics such as different seasonality (i.e. onset, peak, and withdrawal). To investigate the interconnection of different monsoon systems during the pre-industrial Holocene, five transient global climate model simulations have been analysed with respect to the rainfall trend and variability in different sub-domains of the Afro-Asian monsoon region. Our analysis suggests that on millennial timescales with varying orbital forcing, the monsoons do not behave as a tightly connected global system. According to the models, the Indian and North African monsoons are coupled, showing similar rainfall trend and moderate correlation in rainfall variability in all models. The East Asian monsoon changes independently during the Holocene. The dissimilarities in the seasonality of the monsoon sub-systems lead to a stronger response of the North African and Indian monsoon systems to the Holocene insolation forcing than of the East Asian monsoon and affect the seasonal distribution of Holocene rainfall variations. Within the Indian and North African monsoon domain, precipitation solely changes during the summer months, showing a decreasing Holocene precipitation trend. In the East Asian monsoon region, the precipitation signal is determined by an increasing precipitation trend during spring and a decreasing precipitation change during summer, partly balancing each other. A synthesis of reconstructions and the model results do not reveal an impact of the different seasonality on the timing of the Holocene rainfall optimum in the different sub-monsoon systems. They rather indicate locally inhomogeneous rainfall changes and show, that single palaeo-records should not be used to characterise the rainfall change and monsoon evolution for entire monsoon sub-systems.

The evolution of sub-monsoon systems in the Afro-Asian monsoon region during the Holocene- comparison of different transient climate model simulations

NASA Astrophysics Data System (ADS)

Dallmeyer, A.; Claussen, M.; Fischer, N.; Haberkorn, K.; Wagner, S.; Pfeiffer, M.; Jin, L.; Khon, V.; Wang, Y.; Herzschuh, U.

2015-02-01

The recently proposed global monsoon hypothesis interprets monsoon systems as part of one global-scale atmospheric overturning circulation, implying a connection between the regional monsoon systems and an in-phase behaviour of all northern hemispheric monsoons on annual timescales (Trenberth et al., 2000). Whether this concept can be applied to past climates and variability on longer timescales is still under debate, because the monsoon systems exhibit different regional characteristics such as different seasonality (i.e. onset, peak and withdrawal). To investigate the interconnection of different monsoon systems during the pre-industrial Holocene, five transient global climate model simulations have been analysed with respect to the rainfall trend and variability in different sub-domains of the Afro-Asian monsoon region. Our analysis suggests that on millennial timescales with varying orbital forcing, the monsoons do not behave as a tightly connected global system. According to the models, the Indian and North African monsoons are coupled, showing similar rainfall trend and moderate correlation in centennial rainfall variability in all models. The East Asian monsoon changes independently during the Holocene. The dissimilarities in the seasonality of the monsoon sub-systems lead to a stronger response of the North African and Indian monsoon systems to the Holocene insolation forcing than of the East Asian monsoon and affect the seasonal distribution of Holocene rainfall variations. Within the Indian and North African monsoon domain, precipitation solely changes during the summer months, showing a decreasing Holocene precipitation trend. In the East Asian monsoon region, the precipitation signal is determined by an increasing precipitation trend during spring and a decreasing precipitation change during summer, partly balancing each other. A synthesis of reconstructions and the model results do not reveal an impact of the different seasonality on the timing of the Holocene rainfall optimum in the different sub-monsoon systems. Rather they indicate locally inhomogeneous rainfall changes and show that single palaeo-records should not be used to characterise the rainfall change and monsoon evolution for entire monsoon sub-systems.

Rainfall Morphology in Semi-Tropical Convergence Zones

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Ferrier, Brad S.; Ray, Peter S.

2000-01-01

Central Florida is the ideal test laboratory for studying convergence zone-induced convection. The region regularly experiences sea breeze fronts and rainfall-induced outflow boundaries. The focus of this study is the common yet poorly-studied convergence zone established by the interaction of the sea breeze front and an outflow boundary. Previous studies have investigated mechanisms primarily affecting storm initiation by such convergence zones. Few have focused on rainfall morphology yet these storms contribute a significant amount precipitation to the annual rainfall budget. Low-level convergence and mid-tropospheric moisture have both been shown to correlate with rainfall amounts in Florida. Using 2D and 3D numerical simulations, the roles of low-level convergence and mid-tropospheric moisture in rainfall evolution are examined. The results indicate that time-averaged, vertical moisture flux (VMF) at the sea breeze front/outflow convergence zone is directly and linearly proportional to initial condensation rates. This proportionality establishes a similar relationship between VMF and initial rainfall. Vertical moisture flux, which encompasses depth and magnitude of convergence, is better correlated to initial rainfall production than surface moisture convergence. This extends early observational studies which linked rainfall in Florida to surface moisture convergence. The amount and distribution of mid-tropospheric moisture determines how rainfall associated with secondary cells develop. Rainfall amount and efficiency varied significantly over an observable range of relative humidities in the 850- 500 mb layer even though rainfall evolution was similar during the initial or "first-cell" period. Rainfall variability was attributed to drier mid-tropospheric environments inhibiting secondary cell development through entrainment effects. Observationally, 850-500 mb moisture structure exhibits wider variability than lower level moisture, which is virtually always present in Florida. A likely consequence of the variability in 850-500 moisture is a stronger statistical correlation to rainfall, which observational studies have noted. The study indicates that vertical moisture flux forcing at convergence zones is critical in determining rainfall in the initial stage of development but plays a decreasing role in rainfall evolution as the system matures. The mid-tropospheric moisture (e.g. environment) plays an increasing role in rainfall evolution as the system matures. This suggests the need to improve measurements of magnitude/depth of convergence and mid-tropospheric moisture distribution. It also highlights the need for better parameterization of entrainment and vertical moisture distribution in larger-scale models.

A procedure for assessing future trends of subdaily precipitation values on point scale

NASA Astrophysics Data System (ADS)

Rianna, Guido; Villani, Veronica; Mercogliano, Paola; Vezzoli, Renata

2015-04-01

In many areas of Italy, urban flooding or floods in small mountain basins, induced by heavy precipitations on subdaily scale, represent remarkable hazards able to cause huge damages and casualties often increased by very high population density. A proper assessment about how frequency and magnitude of such events could change under the effect of Climate Changes (CC) is crucial for the development of future territorial planning (such as early warning systems). The current constraints of climate modeling, also using high resolution RCM, prevent an adequate representation of subdaily precipitation patterns (mainly concerning extreme values) while available observed datasets are often unsuitable for the application of the bias-correction (BC) techniques requiring long time series. In this work, a new procedure is proposed: at point scale, precipitation outputs on 24 and 48 hours are provided by high resolution (about 8km) climate simulation performed through the RCM COSMO_CLM driven by GCM CMCC_CM and bias-corrected by quantile mapping approach. These ones are adopted for a monthly stochastic disaggregation approach combining Random Parameter Bartlett-Lewis (RPBL) gamma model with appropriate rainfall disaggregation technique. The last one implements empirical correction procedures, called adjusting procedures, to modify the model rainfall output, so that it is consistent with the observed rainfall values on daily time scale. In order to take into account the great difficulties related to minimization of objective function required by retrieving the 7 RPBL parameters, for each dataset the computations are repeated twenty times. Moreover, adopting statistical properties on 24 and 48 hours to retrieve RPBL parameters allows, according Bo et al. (1994), to infer statistical properties until hourly scale maintaining the information content about the possible changes in precipitation patterns due to CC. The entire simulation chain is tested on Baiso weather station, in Northern Italy; the station is representative of a basin of Secchia river, tributary of the Po River; for this station, are available hourly data on 2003-2012 time span while, since 1981, are available daily data and maximum yearly values until hourly scale. In order to evaluate the uncertainties related to stand-alone approach for retrieving hourly data, it is first tested adopting, as input, observed data on 1981-2010 period; after, for the same time interval, RPBL parameters are estimated using BC RCM precipitation data. However, as control, the available hourly data cover only a part of this span. The results show how the approach, in term of mean and maximum values, return satisfying results until 6 hours while for higher resolutions the errors became significant. Finally, in order to assess the possible effects of CC on subdaily precipitation patterns, the same simulation chain is adopted to provide hourly precipitation datasets also for thirty years 2071-2100 under concentration scenarios RCPs 4.5 and RCP 8.5; the comparison between these ones and control period, permits to understand how, in wet season, the expected warming could produce a reduction in mean duration of precipitation events but with higher rainfall intensity; however, during the summer, the strong reduction in precipitation values could deeply affect also hourly values.

Rainfall simulation experiments in the southwestern USA using the Walnut Gulch Rainfall Simulator

NASA Astrophysics Data System (ADS)

Polyakov, Viktor; Stone, Jeffry; Holifield Collins, Chandra; Nearing, Mark A.; Paige, Ginger; Buono, Jared; Gomez-Pond, Rae-Landa

2018-01-01

This dataset contains hydrological, erosion, vegetation, ground cover, and other supplementary information from 272 rainfall simulation experiments conducted on 23 semiarid rangeland locations in Arizona and Nevada between 2002 and 2013. On 30 % of the plots, simulations were conducted up to five times during the decade of study. The rainfall was generated using the Walnut Gulch Rainfall Simulator on 2 m by 6 m plots. Simulation sites included brush and grassland areas with various degrees of disturbance by grazing, wildfire, or brush removal. This dataset advances our understanding of basic hydrological and biological processes that drive soil erosion on arid rangelands. It can be used to estimate runoff, infiltration, and erosion rates at a variety of ecological sites in the Southwestern USA. The inclusion of wildfire and brush treatment locations combined with long-term observations makes it important for studying vegetation recovery, ecological transitions, and the effect of management. It is also a valuable resource for erosion model parameterization and validation. The dataset is available from the National Agricultural Library at https://data.nal.usda.gov/search/type/dataset (DOI: https://doi.org/10.15482/USDA.ADC/1358583).

Mini rainfall simulation for assessing soil erodibility

NASA Astrophysics Data System (ADS)

Peters, Piet; Palese, Dina; Baartman, Jantiene

2016-04-01

The mini rainfall simulator is a small portable rainfall simulator to determine erosion and water infiltration characteristics of soils. The advantages of the mini rainfall simulator are that it is suitable for soil conservation surveys and light and easy to handle in the field. Practical experience over the last decade has shown that the used 'standard' shower is a reliable method to assess differences in erodibility due to soil type and/or land use. The mini rainfall simulator was used recently in a study on soil erosion in olive groves (Ferrandina-Italy). The propensity to erosion of a steep rain-fed olive grove (mean slope ~10%) with a sandy loam soil was evaluated by measuring runoff and sediment load under extreme rain events. Two types of soil management were compared: spontaneous grass as a ground cover (GC) and tillage (1 day (T1) and 10 days after tillage (T2)). Results indicate that groundcover reduced surface runoff to approximately one-third and soil-losses to zero compared with T1. The runoff between the two tilled plots was similar, although runoff on T1 plots increased steadily over time whereas runoff on T2 plots remained stable.

Influence of the Biosphere on Precipitation: July 1995 Studies with the ARM-CART Data

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Mocko, D. M.; Walker, G. K.; Koster, Randal D.

2000-01-01

Ensemble sets of simulation experiments were conducted with a single column model (SCM) using the Goddard GEOS II GCM physics containing a recent version of the Cumulus Scheme (McRAS) and a biosphere based land-fluxes scheme (SSiB). The study used the 18 July to 5 August 1995 ARM-CART (Atmospheric Radiation Measurement-Cloud Atmospheric Radiation Test-bed) data, which was collected at the ARM-CART site in the mid-western United States and analyzed for single column modeling (SCM) studies. The new findings affirm the earlier findings that the vegetation, which increases the solar energy absorption at the surface together with soil and soil-moisture dependent processes, which modulate the surface, fluxes (particularly evapotranspiration) together help to increase the local rainfall. In addition, the results also show that for the particular study period roughly 50% of the increased evaporation over the ARM-CART site would be converted into rainfall with the Column, while the remainder would be advected out to the large-scale. Notwithstanding the limitations of only one-way interaction (i.e., the large-scale influencing the regional physics and not vice versa), the current SCM simulations show a very robust relationship. The evaporation-precipitation relationship turns out to be independent of the soil types, and soil moisture; however, it is weakly dependent on the vegetation cover because of its surface-albedo effect. Clearly, these inferences are prone to weaknesses of the SCM physics, the assumptions of the large-scale being unaffected by gridscale (SCM-scale) changes in moist processes, and other limitations of the evaluation procedures.

Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

A Bayesian beta distribution model for estimating rainfall IDF curves in a changing climate

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; Kwon, Hyun-Han; Kim, Jin-Young

2016-09-01

The estimation of intensity-duration-frequency (IDF) curves for rainfall data comprises a classical task in hydrology studies to support a variety of water resources projects, including urban drainage and the design of flood control structures. In a changing climate, however, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to poor estimates of rainfall intensity quantiles. Climate change scenarios built on General Circulation Models offer a way to access and estimate future changes in spatial and temporal rainfall patterns at the daily scale at the utmost, which is not as fine temporal resolution as required (e.g. hours) to directly estimate IDF curves. In this paper we propose a novel methodology based on a four-parameter beta distribution to estimate IDF curves conditioned on the observed (or simulated) daily rainfall, which becomes the time-varying upper bound of the updated nonstationary beta distribution. The inference is conducted in a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters when building the IDF curves. The proposed model is tested using rainfall data from four stations located in South Korea and projected climate change Representative Concentration Pathways (RCPs) scenarios 6 and 8.5 from the Met Office Hadley Centre HadGEM3-RA model. The results show that the developed model fits the historical data as good as the traditional Generalized Extreme Value (GEV) distribution but is able to produce future IDF curves that significantly differ from the historically based IDF curves. The proposed model predicts for the stations and RCPs scenarios analysed in this work an increase in the intensity of extreme rainfalls of short duration with long return periods.

Mathematical model of sediment and solute transport along slope land in different rainfall pattern conditions

PubMed Central

Tao, Wanghai; Wu, Junhu; Wang, Quanjiu

2017-01-01

Rainfall erosion is a major cause of inducing soil degradation, and rainfall patterns have a significant influence on the process of sediment yield and nutrient loss. The mathematical models developed in this study were used to simulate the sediment and nutrient loss in surface runoff. Four rainfall patterns, each with a different rainfall intensity variation, were applied during the simulated rainfall experiments. These patterns were designated as: uniform-type, increasing-type, increasing- decreasing -type and decreasing-type. The results revealed that changes in the rainfall intensity can have an appreciable impact on the process of runoff generation, but only a slight effect on the total amount of runoff generated. Variations in the rainfall intensity in a rainfall event not only had a significant effect on the process of sediment yield and nutrient loss, but also the total amount of sediment and nutrient produced, and early high rainfall intensity may lead to the most severe erosion and nutrient loss. In this study, the calculated data concur with the measured values. The model can be used to predict the process of surface runoff, sediment transport and nutrient loss associated with different rainfall patterns. PMID:28272431

Assessment of marine weather forecasts over the Indian sector of Southern Ocean

NASA Astrophysics Data System (ADS)

Gera, Anitha; Mahapatra, D. K.; Sharma, Kuldeep; Prakash, Satya; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.; Anilkumar, N.

2017-09-01

The Southern Ocean (SO) is one of the important regions where significant processes and feedbacks of the Earth's climate take place. Expeditions to the SO provide useful data for improving global weather/climate simulations and understanding many processes. Some of the uncertainties in these weather/climate models arise during the first few days of simulation/forecast and do not grow much further. NCMRWF issued real-time five day weather forecasts of mean sea level pressure, surface winds, winds at 500 hPa & 850 hPa and rainfall, daily to NCAOR to provide guidance for their expedition to Indian sector of SO during the austral summer of 2014-2015. Evaluation of the skill of these forecasts indicates possible error growth in the atmospheric model at shorter time scales. The error growth is assessed using the model analysis/reanalysis, satellite data and observations made during the expedition. The observed variability of sub-seasonal rainfall associated with mid-latitude systems is seen to exhibit eastward propagations and are well reproduced in the model forecasts. All cyclonic disturbances including the sub-polar lows and tropical cyclones that occurred during this period were well captured in the model forecasts. Overall, this model performs reasonably well over the Indian sector of the SO in medium range time scale.

Estimating Vegetation Rainfall Interception Using Remote Sensing Observations at Very High Resolution

NASA Astrophysics Data System (ADS)

Cui, Y.; Zhao, P.; Hong, Y.; Fan, W.; Yan, B.; Xie, H.

2017-12-01

Abstract: As an important compont of evapotranspiration, vegetation rainfall interception is the proportion of gross rainfall that is intercepted, stored and subsequently evaporated from all parts of vegetation during or following rainfall. Accurately quantifying the vegetation rainfall interception at a high resolution is critical for rainfall-runoff modeling and flood forecasting, and is also essential for understanding its further impact on local, regional, and even global water cycle dynamics. In this study, the Remote Sensing-based Gash model (RS-Gash model) is developed based on a modified Gash model for interception loss estimation using remote sensing observations at the regional scale, and has been applied and validated in the upper reach of the Heihe River Basin of China for different types of vegetation. To eliminate the scale error and the effect of mixed pixels, the RS-Gash model is applied at a fine scale of 30 m with the high resolution vegetation area index retrieved by using the unified model of bidirectional reflectance distribution function (BRDF-U) for the vegetation canopy. Field validation shows that the RMSE and R2 of the interception ratio are 3.7% and 0.9, respectively, indicating the model's strong stability and reliability at fine scale. The temporal variation of vegetation rainfall interception loss and its relationship with precipitation are further investigated. In summary, the RS-Gash model has demonstrated its effectiveness and reliability in estimating vegetation rainfall interception. When compared to the coarse resolution results, the application of this model at 30-m fine resolution is necessary to resolve the scaling issues as shown in this study. Keywords: rainfall interception; remote sensing; RS-Gash analytical model; high resolution

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2003-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data fiom the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo- China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the lowlevel temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation.

Spatial structure of monthly rainfall measurements average over 25 years and trends of the hourly variability of a current rainy day in Rwanda.

NASA Astrophysics Data System (ADS)

Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

2013-04-01

Climate plays a vital role in a wide range of socio-economic activities of most nations particularly of developing countries. Climate (rainfall) plays a central role in agriculture which is the main stay of the Rwandan economy and community livelihood and activities. The majority of the Rwandan population (81,1% in 2010) relies on rain fed agriculture for their livelihoods, and the impacts of variability in climate patterns are already being felt. Climate-related events like heavy rainfall or too little rainfall are becoming more frequent and are impacting on human wellbeing.The torrential rainfall that occurs every year in Rwanda could disturb the circulation for many days, damages houses, infrastructures and causes heavy economic losses and deaths. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). Globally, the spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front» mechanism. What is the hourly variability in this mountainous area? Is there any correlation with the identified zones of the monthly average series (from 1965 to 1990 established by the Rwandan meteorological services)? Where could we have hazards with several consecutive rainy days (using forecasted datas from the Norwegian Meteorological Institute)? Spatio-temporal analysis allows for identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting these hydrological events. The objective of our current research (Rainfall variability) is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. Hybrid models - mixing geostatistics and machine learning, will be applied to study spatial non-stationarity of rainfall fields. The research will include rainfalls variability mapping and probabilistic analyses of extreme events. Key words: rainfall variability, Rwanda, extreme event, model, mapping, geostatistics.

Analysis of convection-permitting simulations for capturing heavy rainfall events over Myanmar Region

NASA Astrophysics Data System (ADS)

Acierto, R. A. E.; Kawasaki, A.

2017-12-01

Perennial flooding due to heavy rainfall events causes strong impacts on the society and economy. With increasing pressures of rapid development and potential for climate change impacts, Myanmar experiences a rapid increase in disaster risk. Heavy rainfall hazard assessment is key on quantifying such disaster risk in both current and future conditions. Downscaling using Regional Climate Models (RCM) such as Weather Research and Forecast model have been used extensively for assessing such heavy rainfall events. However, usage of convective parameterizations can introduce large errors in simulating rainfall. Convective-permitting simulations have been used to deal with this problem by increasing the resolution of RCMs to 4km. This study focuses on the heavy rainfall events during the six-year (2010-2015) wet period season from May to September in Myanmar. The investigation primarily utilizes rain gauge observation for comparing downscaled heavy rainfall events in 4km resolution using ERA-Interim as boundary conditions using 12km-4km one-way nesting method. The study aims to provide basis for production of high-resolution climate projections over Myanmar in order to contribute for flood hazard and risk assessment.

Stochastically-forced Decadal Variability in Australian Rainfall

NASA Astrophysics Data System (ADS)

Taschetto, A.

2015-12-01

Iconic Australian dry and wet periods were driven by anomalous conditions in the tropical oceans, such as the worst short-term drought in the southeast in 1982 associated with the strong El Niño and the widespread "Big Wet" in 1974 linked with a La Niña event. The association with oceanic conditions makes droughts predictable to some extent. However, prediction can be difficult when there is no clear external forcing such as El Niños. Can dry spells be triggered and maintained with no ocean memory? In this study, we investigate the potential role of internal multi-century atmospheric variability in controlling the frequency, duration and intensity of long-term dry and wet spells over Australia. Two multi-century-scale simulations were performed with the NCAR CESM: (1) a fully-coupled simulation (CPLD) and (2) an atmospheric simulation forced by a seasonal SST climatology derived from the coupled experiment (ACGM). Results reveal that droughts and wet spells can indeed be generated by internal variability of the atmosphere. Those internally generated events are less severe than those forced by oceanic variability, however the duration of dry and wet spells longer than 3 years is comparable with and without the ocean memory. Large-scale ocean modes of variability seem to play an important role in producing continental-scale rainfall impacts over Australia. While the Pacific Decadal Oscillation plays an important role in generating droughts in the fully coupled model, perturbations of monsoonal winds seem to be the main trigger of dry spells in the AGCM case. Droughts in the mid-latitude regions such as Tasmania can be driven by perturbations in the Southern Annular Mode, not necessarily linked to oceanic conditions even in the fully-coupled model. The mechanisms behind internally-driven mega-droughts and mega-wets will be discussed.

Sensitivity of convective precipitation to soil moisture and vegetation during break spell of Indian summer monsoon

NASA Astrophysics Data System (ADS)

Kutty, Govindan; Sandeep, S.; Vinodkumar; Nhaloor, Sreejith

2017-07-01

Indian summer monsoon rainfall is characterized by large intra-seasonal fluctuations in the form of active and break spells in rainfall. This study investigates the role of soil moisture and vegetation on 30-h precipitation forecasts during the break monsoon period using Weather Research and Forecast (WRF) model. The working hypothesis is that reduced rainfall, clear skies, and wet soil condition during the break monsoon period enhance land-atmosphere coupling over central India. Sensitivity experiments are conducted with modified initial soil moisture and vegetation. The results suggest that an increase in antecedent soil moisture would lead to an increase in precipitation, in general. The precipitation over the core monsoon region has increased by enhancing forest cover in the model simulations. Parameters such as Lifting Condensation Level, Level of Free Convection, and Convective Available Potential Energy indicate favorable atmospheric conditions for convection over forests, when wet soil conditions prevail. On spatial scales, the precipitation is more sensitive to soil moisture conditions over northeastern parts of India. Strong horizontal gradient in soil moisture and orographic uplift along the upslopes of Himalaya enhanced rainfall over the east of Indian subcontinent.

Slope-velocity equilibrium and evolution of surface roughness on a stony hillslope

NASA Astrophysics Data System (ADS)

Nearing, Mark A.; Polyakov, Viktor O.; Nichols, Mary H.; Hernandez, Mariano; Li, Li; Zhao, Ying; Armendariz, Gerardo

2017-06-01

Slope-velocity equilibrium is hypothesized as a state that evolves naturally over time due to the interaction between overland flow and surface morphology, wherein steeper areas develop a relative increase in physical and hydraulic roughness such that flow velocity is a unique function of overland flow rate independent of slope gradient. This study tests this hypothesis under controlled conditions. Artificial rainfall was applied to 2 m by 6 m plots at 5, 12, and 20 % slope gradients. A series of simulations were made with two replications for each treatment with measurements of runoff rate, velocity, rock cover, and surface roughness. Velocities measured at the end of each experiment were a unique function of discharge rates, independent of slope gradient or rainfall intensity. Physical surface roughness was greater at steeper slopes. The data clearly showed that there was no unique hydraulic coefficient for a given slope, surface condition, or rainfall rate, with hydraulic roughness greater at steeper slopes and lower intensities. This study supports the hypothesis of slope-velocity equilibrium, implying that use of hydraulic equations, such as Chezy and Manning, in hillslope-scale runoff models is problematic because the coefficients vary with both slope and rainfall intensity.

Aspect of ECMWF downscaled Regional Climate Modeling in simulating Indian summer monsoon rainfall and dependencies on lateral boundary conditions

NASA Astrophysics Data System (ADS)

Ghosh, Soumik; Bhatla, R.; Mall, R. K.; Srivastava, Prashant K.; Sahai, A. K.

2018-03-01

Climate model faces considerable difficulties in simulating the rainfall characteristics of southwest summer monsoon. In this study, the dynamical downscaling of European Centre for Medium-Range Weather Forecast's (ECMWF's) ERA-Interim (EIN15) has been utilized for the simulation of Indian summer monsoon (ISM) through the Regional Climate Model version 4.3 (RegCM-4.3) over the South Asia Co-Ordinated Regional Climate Downscaling EXperiment (CORDEX) domain. The complexities of model simulation over a particular terrain are generally influenced by factors such as complex topography, coastal boundary, and lack of unbiased initial and lateral boundary conditions. In order to overcome some of these limitations, the RegCM-4.3 is employed for simulating the rainfall characteristics over the complex topographical conditions. For reliable rainfall simulation, implementations of numerous lower boundary conditions are forced in the RegCM-4.3 with specific horizontal grid resolution of 50 km over South Asia CORDEX domain. The analysis is considered for 30 years of climatological simulation of rainfall, outgoing longwave radiation (OLR), mean sea level pressure (MSLP), and wind with different vertical levels over the specified region. The dependency of model simulation with the forcing of EIN15 initial and lateral boundary conditions is used to understand the impact of simulated rainfall characteristics during different phases of summer monsoon. The results obtained from this study are used to evaluate the activity of initial conditions of zonal wind circulation speed, which causes an increase in the uncertainty of regional model output over the region under investigation. Further, the results showed that the EIN15 zonal wind circulation lacks sufficient speed over the specified region in a particular time, which was carried forward by the RegCM output and leads to a disrupted regional simulation in the climate model.

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania

PubMed Central

Tumbo, S. D.; Kihupi, N. I.; Rwehumbiza, Filbert B.

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly. PMID:28536708

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

PubMed

Msongaleli, Barnabas M; Tumbo, S D; Kihupi, N I; Rwehumbiza, Filbert B

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly.

Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

NASA Astrophysics Data System (ADS)

Li, Y.; Kurkute, S.; Chen, L.

2017-12-01

Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

Idealized Cloud-System Resolving Modeling for Tropical Convection Studies

NASA Astrophysics Data System (ADS)

Anber, Usama M.

A three-dimensional limited-domain Cloud-Resolving Model (CRM) is used in idealized settings to study the interaction between tropical convection and the large scale dynamics. The model domain is doubly periodic and the large-scale circulation is parameterized using the Weak Temperature Gradient (WTG) Approximation and Damped Gravity Wave (DGW) methods. The model simulations fall into two main categories: simulations with a prescribed radiative cooling profile, and others in which radiative cooling profile interacts with clouds and water vapor. For experiments with a prescribed radiative cooling profile, radiative heating is taken constant in the vertical in the troposphere. First, the effect of turbulent surface fluxes and radiative cooling on tropical deep convection is studied. In the precipitating equilibria, an increment in surface fluxes produces a greater increase in precipitation than an equal increment in column-integrated radiative heating. The gross moist stability remains close to constant over a wide range of forcings. With dry initial conditions, the system exhibits hysteresis, and maintains a dry state with for a wide range of net energy inputs to the atmospheric column under WTG. However, for the same forcings the system admits a rainy state when initialized with moist conditions, and thus multiple equilibria exist under WTG. When the net forcing is increased enough that simulations, which begin dry, eventually develop precipitation. DGW, on the other hand, does not have the tendency to develop multiple equilibria under the same conditions. The effect of vertical wind shear on tropical deep convection is also studied. The strength and depth of the shear layer are varied as control parameters. Surface fluxes are prescribed. For weak wind shear, time-averaged rainfall decreases with shear and convection remains disorganized. For larger wind shear, rainfall increases with shear, as convection becomes organized into linear mesoscale systems. This non-monotonic dependence of rainfall on shear is observed when the imposed surface fluxes are moderate. For larger surface fluxes, convection in the unsheared basic state is already strongly organized, but increasing wind shear still leads to increasing rainfall. In addition to surface rainfall, the impacts of shear on the parameterized large-scale vertical velocity, convective mass fluxes, cloud fraction, and momentum transport are also discussed. For experiments with interactive radiative cooling profile, the effect of cloud-radiation interaction on cumulus ensemble is examined in sheared and unsheared environments with both fixed and interactive sea surface temperature (SST). For fixed SST, interactive radiation, when compared to simulations in which radiative profile has the same magnitude and vertical shape but does not interact with clouds or water vapor, is found to suppress mean precipitation by inducing strong descent in the lower troposphere, increasing the gross moist stability. For interactive SST, using a slab ocean mixed layer, there exists a shear strength above which the system becomes unstable and develops oscillatory behavior. Oscillations have periods of wet precipitating states followed by periods of dry non-precipitating states. The frequencies of oscillations are intraseasonal to subseasonal, depending on the mixed layer depth. Finally, the model is coupled to a land surface model with fully interactive radiation and surface fluxes to study the diurnal and seasonal radiation and water cycles in the Amazon basin. The model successfully captures the afternoon precipitation and cloud cover peak and the greater latent heat flux in the dry season for the first time; two major biases in GCMs with implications for correct estimates of evaporation and gross primary production in the Amazon. One of the key findings is that the fog layer near the surface in the west season is crucial for determining the surface energy budget and precipitation. This suggests that features on the diurnal time scale can significantly impact climate on the seasonal time scale.

Groundwater recharge estimation under semi arid climate: Case of Northern Gafsa watershed, Tunisia

NASA Astrophysics Data System (ADS)

Melki, Achraf; Abdollahi, Khodayar; Fatahi, Rouhallah; Abida, Habib

2017-08-01

Natural groundwater recharge under semi arid climate, like rainfall, is subjected to large variations in both time and space and is therefore very difficult to predict. Nevertheless, in order to set up any strategy for water resources management in such regions, understanding the groundwater recharge variability is essential. This work is interested in examining the impact of rainfall on the aquifer system recharge in the Northern Gafsa Plain in Tunisia. The study is composed of two main parts. The first is interested in the analysis of rainfall spatial and temporal variability in the study basin while the second is devoted to the simulation of groundwater recharge. Rainfall analysis was performed based on annual precipitation data recorded in 6 rainfall stations over a period of 56 years (1960-2015). Potential evapotranspiration data were also collected from 1960 to 2011 (52 years). The hydrologic distributed model WetSpass was used for the estimation of groundwater recharge. Model calibration was performed based on an assessment of the agreement between the sum of recharge and runoff values estimated by the WetSpass hydrological model and those obtained by the climatic method. This latter is based on the difference calculated between rainfall and potential evapotranspiration recorded at each rainy day. Groundwater recharge estimation, on monthly scale, showed that average annual precipitation (183.3 mm/year) was partitioned to 5, 15.3, 36.8, and 42.8% for interception, runoff, actual evapotranspiration and recharge respectively.

Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

2016-04-01

The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the Mediterranean area. This spatio-temporal analysis of rainfall erosivity at European scale is very important for policy makers and farmers for soil conservation, optimization of agricultural land use and natural hazards prediction. REDES is also used in combination with future rainfall data from WorldClim to run climate change scenarios. The projection of REDES combined with climate change scenarios (HADGEM2, RCP4.5) and using a robust geo-statistical model resulted in a 10-20% increase of the R-factor in Europe till 2050.

Relationships between southeastern Australian rainfall and sea surface temperatures examined using a climate model

NASA Astrophysics Data System (ADS)

Watterson, I. G.

2010-05-01

Rainfall in southeastern Australia has declined in recent years, particularly during austral autumn over the state of Victoria. A recent study suggests that sea surface temperature (SST) variations in both the Indonesian Throughflow (ITF) region and in a meridional dipole in the central Indian Ocean have influenced Victorian late autumn rainfall since 1950. However, it remains unclear to what extent SSTs in these and other regions force such a teleconnection. Analysis of a 1080 year simulation by the climate model CSIRO Mk3.5 shows that the model Victorian rainfall is correlated rather realistically with SSTs but that part of the above relationships is due to the model ENSO. Furthermore, the remote patterns of pressure, rainfall, and land temperature greatly diminish when the data are lagged by 1 month, suggesting that the true forcing by the persisting SSTs is weak. In a series of simulations of the atmospheric Mk3.5 with idealized SST anomalies, raised SSTs to the east of Indonesia lower the simulated Australian rainfall, while those to the west raise it. A positive ITF anomaly lowers pressure over Australia, but with little effect on Victorian rainfall. The meridional dipole and SSTs to the west and southeast of Australia have little direct effect on southeastern Australia in the model. The results suggest that tropical SSTs predominate as an influence on Victorian rainfall. However, the SST indices appear to explain only a fraction of the observed trend, which in the case of decadal means remains within the range of unforced variability simulated by Mk3.5.

The soil-water balance simulations of a grassland in response to CO2, rainfall, and biodiversity manipulations at BioCON

NASA Astrophysics Data System (ADS)

Flinker, R. H.; Cardenas, M.; Caldwell, T. G.; Rich, R.; Reich, P.

2013-12-01

The BioCON (Biodiversity, CO2 and N) experiment has been continuously running since 1997. Operated by the University of Minnesota and located within the Cedar Creek Ecosystem Science Reserve in Minnesota, USA, BioCON is a Free-Air CO2 Enrichment (FACE) experiment that investigates plant community response to three key environmental variables: nitrogen, atmospheric CO2 and biodiversity. More recently rainfall exclusion and temperature manipulation were added to the experiment which amounts to 371 plots. The site attempts to replicate predicted average temperature increases and a northern shift of plant species and any associated consequences. FACE experiments have been conducted for a number of years in different countries, but the focus has generally been on how plant communities, soil respiration and microbes respond. Minimal work has been focused on the hydrologic aspects of these experiments which are potentially valuable for investigating global warming effects on local and plot-scale ecohydrology. Thus, the objective of this work is to characterize and model unsaturated flow for different CO2 and rainfall treatments in order to see how they affect soil moisture dynamics and groundwater recharge on grasslands of central Minnesota. Our study focuses on simulating soil moisture dynamics in eighteen of the BioCON plots: six bare plots with regular rainfall regimes (zero plant species, three plots with elevated atmospheric CO2 levels), six regular rainfall regimes (nine plant species, three plots with elevated atmospheric CO2 levels) and six reduced rainfall regimes (nine plant species, three plots with elevated atmospheric CO2 levels). The Simultaneous Heat and Water (SHAW) model, which solves the Richards equation for unsaturated zone water flow coupled to a comprehensive energy balance model, was parameterized with a combination of field and lab estimates of soil properties. Field estimates of saturated hydraulic conductivity using tension infiltrometers ranged from 9.8 x 10-4 to 6.7 x 10-3 cm/s. Soil cores were collected and analyzed for soil hydraulic properties (texture, unsaturated hydraulic conductivity and moisture retention). From the grain size analyzes of soil samples collected every 10 cm until 1m depth, the soil is homogenous and on average 87% sand, 11% silt and 2% clay. We will be presenting results from the simulations and statistical comparisons to observations of soil moisture at four depths in each plot.

Evaluation and projected changes of precipitation statistics in convection-permitting WRF climate simulations over Central Europe

NASA Astrophysics Data System (ADS)

Knist, Sebastian; Goergen, Klaus; Simmer, Clemens

2018-02-01

We perform simulations with the WRF regional climate model at 12 and 3 km grid resolution for the current and future climates over Central Europe and evaluate their added value with a focus on the daily cycle and frequency distribution of rainfall and the relation between extreme precipitation and air temperature. First, a 9 year period of ERA-Interim driven simulations is evaluated against observations; then global climate model runs (MPI-ESM-LR RCP4.5 scenario) are downscaled and analyzed for three 12-year periods: a control, a mid-of-century and an end-of-century projection. The higher resolution simulations reproduce both the diurnal cycle and the hourly intensity distribution of precipitation more realistically compared to the 12 km simulation. Moreover, the observed increase of the temperature-extreme precipitation scaling from the Clausius-Clapeyron (C-C) scaling rate of 7% K-1 to a super-adiabatic scaling rate for temperatures above 11 °C is reproduced only by the 3 km simulation. The drop of the scaling rates at high temperatures under moisture limited conditions differs between sub-regions. For both future scenario time spans both simulations suggest a slight decrease in mean summer precipitation and an increase in hourly heavy and extreme precipitation. This increase is stronger in the 3 km runs. Temperature-extreme precipitation scaling curves in the future climate are projected to shift along the 7% K-1 trajectory to higher peak extreme precipitation values at higher temperatures. The curves keep their typical shape of C-C scaling followed by super-adiabatic scaling and a drop-off at higher temperatures due to moisture limitation.

The development of a sub-daily gridded rainfall product to improve hydrological predictions in Great Britain

NASA Astrophysics Data System (ADS)

Quinn, Niall; Freer, Jim; Coxon, Gemma; O'Loughlin, Fiachra; Woods, Ross; Liguori, Sara

2015-04-01

In Great Britain and many other regions of the world, flooding resulting from short duration, high intensity rainfall events can lead to significant economic losses and fatalities. At present, such extreme events are often poorly evaluated using hydrological models due, in part, to their rarity and relatively short duration and a lack of appropriate data. Such storm characteristics are not well represented by daily rainfall records currently available using volumetric gauges and/or derived gridded products. This research aims to address this important data gap by developing a sub-daily gridded precipitation product for Great Britain. Our focus is to better understand these storm events and some of the challenges and uncertainties in quantifying such data across catchment scales. Our goal is to both improve such rainfall characterisation and derive an input to drive hydrological model simulations. Our methodology involves the collation, error checking, and spatial interpolation of approximately 2000 rain gauges located across Great Britain, provided by the Scottish Environment Protection Agency (SEPA) and the Environment Agency (EA). Error checking was conducted over the entirety of the TBR data available, utilising a two stage approach. First, rain gauge data at each site were examined independently, with data exceeding reasonable thresholds marked as suspect. Second, potentially erroneous data were marked using a neighbourhood analysis approach whereby measurements at a given gauge were deemed suspect if they did not fall within defined bounds of measurements at neighbouring gauges. A total of eight error checks were conducted. To provide the user with the greatest flexibility possible, the error markers associated with each check have been recorded at every site. This approach aims to enable the user to choose which checks they deem most suitable for a particular application. The quality assured TBR dataset was then spatially interpolated to produce a national scale gridded rainfall product. Finally, radar rainfall data provided by the UK Met Office was assimilated, where available, to provide an optimal hourly estimate of rainfall, given the error variance associated with both datasets. This research introduces a sub-daily rainfall product that will be of particular value to hydrological modellers requiring rainfall inputs at higher temporal resolutions than those currently available nationally. Further research will aim to quantify the uncertainties in the rainfall product in order to improve our ability to diagnose and identify structural errors in hydrological modelling of extreme events. Here we present our initial findings.

The Role of Low-Level, Terrain-Induced Jets in Rainfall Variability in Tigris Euphrates Headwaters

NASA Technical Reports Server (NTRS)

Dezfuli, Amin K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Evans, Jason; Peters-Lidard, Christa D.

2017-01-01

Rainfall variability in the Tigris Euphrates headwaters is a result of interaction between topography and meteorological features at a range of spatial scales. Here, the Weather Research and Forecasting (WRF) Model, driven by the NCEP-DOE AMIP-II reanalysis (R-2), has been implemented to better understand these interactions. Simulations were performed over a domain covering most of the Middle East. The extended simulation period (1983 - 2013) enables us to study seasonality, interannual variability, spatial variability, and extreme events of rainfall. Results showed that the annual cycle of precipitation produced by WRF agrees much more closely with observations than does R-2. This was particularly evident during the transition months of April and October, which were further examined to study the underlying physical mechanisms. In both months, WRF improves representation of interannual variability relative to R-2, with a substantially larger benefit in April. This improvement results primarily from WRFs ability to resolve two low-level, terrain-induced flows in the region that are either absent or weak in R-2: one parallel to the western edge of the Zagros Mountains, and one along the east Turkish highlands. The first shows a complete reversal in its direction during wet and dry days, when flowing southeasterly it transports moisture from the Persian Gulf to the region, and when flowing northwesterly it blocks moisture and transports it away from the region. The second is more directly related to synoptic-scale systems and carries moist, warm air from the Mediterranean and Red Seas toward the region. The combined contribution of these flows explains about 50 of interannual variability in both WRF and observations for April and October precipitation.

The role of low-level terrain-induced jets in rainfall variability in Tigris-Euphrates Headwaters

PubMed Central

Zaitchik, Benjamin F.; Badr, Hamada S.; Evans, Jason; Peters-Lidard, Christa D.

2018-01-01

Rainfall variability in the Tigris-Euphrates Headwaters is a result of interaction between topography and meteorological features at a range of spatial scales. Here, we have implemented the Weather Research and Forecasting (WRF) model, driven by NCEP/DOE R2, to better understand these interactions. Simulations were performed over a domain covering most of the Middle-East. The extended simulation period (1983–2013) enables us to study seasonality, interannual variability, spatial variability and extreme events of rainfall. Results showed that the annual cycle of precipitation produced by WRF agrees much more closely with observations than does R2. This was particularly evident during the transition months of April and October, which were further examined to study the underlying physical mechanisms. In both months, WRF improves representation of interannual variability relative to R2, with a substantially larger benefit in April. This improvement results primarily from WRF’s ability to resolve two low-level terrain-induced flows in the region that are either absent or weak in NCEP/DOE: one parallel to western edge of the Zagros Mountains, and one along the East Turkish Highlands. The first shows a complete reversal in its direction during wet and dry days: when flowing southeasterly it transports moisture from the Persian Gulf to the region, and when flowing northwesterly it blocks moisture and transports it away from the region. The second is more directly related to synoptic-scale systems and carries moist, warm air from the Mediterranean and Red Seas toward the region. The combined contribution of these flows explains about 50% of interannual variability in both WRF and observations for April and October precipitation. PMID:29726552

Analysis and hindcast simulations of an extreme rainfall event in the Mediterranean area: The Genoa 2011 case

NASA Astrophysics Data System (ADS)

Fiori, E.; Comellas, A.; Molini, L.; Rebora, N.; Siccardi, F.; Gochis, D. J.; Tanelli, S.; Parodi, A.

2014-03-01

The city of Genoa, which places between the Tyrrhenian Sea and the Apennine mountains (Liguria, Italy) was rocked by severe flash floods on the 4th of November, 2011. Nearly 500 mm of rain, a third of the average annual rainfall, fell in six hours. Six people perished and millions of Euros in damages occurred. The synoptic-scale meteorological system moved across the Atlantic Ocean and into the Mediterranean generating floods that killed 5 people in Southern France, before moving over the Ligurian Sea and Genoa producing the extreme event studied here. Cloud-permitting simulations (1 km) of the finger-like convective system responsible for the torrential event over Genoa have been performed using Advanced Research Weather and Forecasting Model (ARW-WRF, version 3.3). Two different microphysics (WSM6 and Thompson) as well as three different convection closures (explicit, Kain-Fritsch, and Betts-Miller-Janjic) were evaluated to gain a deeper understanding of the physical processes underlying the observed heavy rain event and the model's capability to predict, in hindcast mode, its structure and evolution. The impact of forecast initialization and of model vertical discretization on hindcast results is also examined. Comparison between model hindcasts and observed fields provided by raingauge data, satellite data, and radar data show that this particular event is strongly sensitive to the details of the mesoscale initialization despite being evolved from a relatively large scale weather system. Only meso-γ details of the event were not well captured by the best setting of the ARW-WRF model and so peak hourly rainfalls were not exceptionally well reproduced. The results also show that specification of microphysical parameters suitable to these events have a positive impact on the prediction of heavy precipitation intensity values.

The Role of Low-Level Terrain-Induced Jets in Rainfall Variability in Tigris-Euphrates Headwaters

NASA Technical Reports Server (NTRS)

Dezfuli, Amin K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Evans, Jason; Peters-Lidard, Christa D.

2017-01-01

Rainfall variability in the Tigris-Euphrates headwaters is a result of interaction between topography and meteorological features at a range of spatial scales. Here, the Weather Research and Forecasting (WRF) Model, driven by the NCEPDOE AMIP-II reanalysis (R-2), has been implemented to better understand these interactions. Simulations were performed over a domain covering most of the Middle East. The extended simulation period (19832013) enables us to study seasonality, interannual variability, spatial variability, and extreme events of rainfall. Results showed that the annual cycle of precipitation produced by WRF agrees much more closely with observations than does R-2. This was particularly evident during the transition months of April and October, which were further examined to study the underlying physical mechanisms. In both months, WRF improves representation of interannual variability relative to R-2, with a substantially larger benefit in April. This improvement results primarily from WRFs ability to resolve two low-level, terrain-induced flows in the region that are either absent or weak in R-2: one parallel to the western edge of the Zagros Mountains, and one along the east Turkish highlands. The first shows a complete reversal in its direction during wet and dry days: when flowing southeasterly it transports moisture from the Persian Gulf to the region, and when flowing northwesterly it blocks moisture and transports it away from the region. The second is more directly related to synoptic-scale systems and carries moist, warm air from the Mediterranean and Red Seas toward the region. The combined contribution of these flows explains about 50 of interannual variability in both WRF and observations for April and October precipitation.

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

2008-01-01

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Trend and variability in western and central Africa streamflow, and major drivers of variability between 1950 and 2005

NASA Astrophysics Data System (ADS)

Dieppois, B.; Sidibe, M.; Mahe, G. M.; Paturel, J. E.; Anifowose, B. A.; Lawler, D.; Amoussou, E.

2017-12-01

Unprecedented drought episodes that struck western and central Africa between the late 1960s and 1980s, triggered many studies investigating rainfall variability and its impacts on water resources and food production systems. However, most studies were focused at the catchment scale. In this study, we aim at investigating the key large-scale controls determining and modulating climate-river flows relationships at the subcontinental scale between 1950 and 2005. Using the first complete monthly streamflow data set (1950-2005) over western and central Africa, streamflow trend and variability are seasonally assessed at this subcontinental scale and compared to those observed in other hydroclimatic variables (precipitation, temperature and potential evapotranspiration). Long-term trends and variability in streamflow are mainly consistent with trends in rainfall. In particular, the recent post-1990s partial recovery in Sahel rainfall could have, at least partially, positively impacted river flows (e.g. the Senegal and Niger rivers). However, these relationships may have been moderated by: i) changes in land use; and ii) contributions from groundwater resources. In addition, the time-evolution of river flows is shown to be primarily driven by very strong decadal fluctuations, which can be interpreted as modulations in the baseflow, as determined using multi-temporal trend and continuous wavelet analysis. These decadal fluctuations, which are also significantly detected in rainfall, are likely related to large-scale sea-surface temperature (SST) anomaly patterns (such as the tropical Atlantic SST variability, the Atlantic Multidecadal Oscillation, the Interdecadal Pacific Oscillation and the Pacific Decadal Oscillation), which are together modulating the West African monsoon. Furthermore, influences of the catchment properties (e.g. size, vegetation and land use cover, soil properties, direction of stream flow across climate zones) on these decadal fluctuations in river flows have been examined. This study therefore aims to improve the ability of current global to regional climate models to simulate such ranges of variability and understand regional hydroclimate, as a means for improving the development of future scenarios for water resources in western and central Africa.

Cascade rainfall disaggregation application in U.S. Central Plains

USDA-ARS?s Scientific Manuscript database

Hourly rainfall are increasingly used in complex, process-based simulations of the environment. Long records of daily rainfall are common, but long continuous records of hourly rainfall are rare and must be developed. A Multiplicative Random Cascade (MRC) model is proposed to disaggregate observed d...

A simplified rainfall-runoff stochastic simulation method for an application of the SCHADEX method to ungauged catchments.

NASA Astrophysics Data System (ADS)

Penot, David; Paquet, Emmanuel; Lang, Michel

2014-05-01

SCHADEX is a probabilistic method for extreme flood estimation, developed and applied since 2006 at Electricité de France (EDF) for dam spillway design [Paquet et al., 2013]. SCHADEX is based on a semi-continuous rainfall-runoff simulation process. The method has been built around two models: a Multi-Exponential Weather Pattern (MEWP) distribution for rainfall probability estimation [Garavaglia et al., 2010] and the MORDOR hydrological model. To use SCHADEX in ungauged context, rainfall distribution and hydrological model must be regionalized. The regionalization of the MEWP rainfall distribution can be managed with SPAZM, a daily rainfall interpolator [Gottardi et al., 2012] which provides reasonable estimates of point and areal rainfall up to hight quantiles. The main issue remains to regionalize MORDOR which is heavily parametrized. A much more simple model has been considered: the SCS model. It is a well known model for event simulation [USDA SCS, 1985; Beven, 2003] and it relies on only one parameter. Then, the idea is to use the SCS model instead of MORDOR within a simplified stochastic simulation scheme to produce a distribution of flood volume from an exhaustive crossing between rainy events and catchment saturation hazards. The presentation details this process and its capacity to generate a runoff distribution based on catchment areal rainfall distribution. The simulation method depends on a unique parameter Smax, the maximum initial loss of the catchment. Then an initial loss S (between zero and Smax) can be drawn to account for the variability of catchment state (between dry and saturated). The distribution of initial loss (or conversely, of catchment saturation, as modeled by MORDOR) seems closely linked to the catchment's regime, therefore easily to regionalize. The simulation takes into account a snow contribution for snow driven catchments, and an antecedent runoff. The presentation shows the results of this stochastic procedure applied on 80 French catchments and its capacity to represent the asymptotic behaviour of the runoff distribution. References: K. J. Beven. Rainfall-Runoff modelling The Primer, British Library, 2003. F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara. Introducing a rainfall compound distribution model based on weather patterns sub-sampling. Hydrology and Earth System Sciences, 14(6):951-964, 2010. F. Gottardi, C. Obled, J. Gailhard, and E. Paquet. Statistical reanalysis of precipitation fields based on ground network data and weather patterns : Application over french mountains. Journal of Hydrology, 432-433:154-167, 2012. ISSN 0022-1694. E. Paquet, F. Garavaglia, R Garçon, and J. Gailhard. The schadex method : a semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 2013. USDA SCS, National Engineering Handbook, Supplement A, Section 4, Chapter 10. Whashington DC, 1985.

Possible impacts of the pre-monsoon dry line and sea breeze front on nocturnal rainfall over northeast Bangladesh

NASA Astrophysics Data System (ADS)

Stiller-Reeve, Mathew; Toniazzo, Thomas; Kolstad, Erik; Spengler, Thomas

2017-04-01

The northeast region of Bangladesh receives a large amount of rainfall before the large-scale monsoon circulation begins. For example, in April (a "pre-monsoon" month) 2010, 804 mm of rain fell in the regional capital Sylhet. It was the second wettest month of the entire year. From our conversations with the local people, we know that this pre-monsoon rainfall is extremely important to their livelihoods. We therefore need to understand it's triggering mechanisms. Several theories have been published, all of which are likely to be at play. However, in this work we look more closely at how the sea breeze front and prominent pre-monsoonal dry line in this region may play a role. If these mechanisms play a role in the convection, then it is likely that they trigger convection further afield, and then the resulting systems then propagate towards northeast Bangladesh. We believe this because rainfall associated with dry line/sea-breeze front convection often occurs during the late afternoon, but the rainfall over northeast Bangladesh shows a clear late-night/early-morning maxima. At present, the temporal and spatial resolution of the regional observations is inappropriate for examining these possible mechanisms. We therefore use a numerical model (WRF) to investigate the possible links between the convection and the sea breeze front and dry line. We use April 2010 as a case study since it was such a wet pre-monsoon month. The simulation shows that a sea breeze circulation often develops during the day in the coastal zone of Bangladesh and northeast India. After sunset the sea breeze front propagates inland pushing back the hot, dry air over India. On several days during the simulation, convection is triggered along the sea breeze front, which then propagates towards northeast Bangladesh and intensifies across the topography surrounding the Sylhet region. From our simulations, it appears that nocturnal convection over northeast Bangladesh is triggered by several mechanisms, but that the dry line and sea breeze front could also be an active contributor.

Effects of rainfall spatial variability and intermittency on shallow landslide triggering patterns at a catchment scale

NASA Astrophysics Data System (ADS)

von Ruette, J.; Lehmann, P.; Or, D.

2014-10-01

The occurrence of shallow landslides is often associated with intense and prolonged rainfall events, where infiltrating water reduces soil strength and may lead to abrupt mass release. Despite general understanding of the role of rainfall water in slope stability, the prediction of rainfall-induced landslides remains a challenge due to natural heterogeneity that affect hydrologic loading patterns and the largely unobservable internal progressive failures. An often overlooked and potentially important factor is the role of rainfall variability in space and time on landslide triggering that is often obscured by coarse information (e.g., hourly radar data at spatial resolution of a few kilometers). To quantify potential effects of rainfall variability on failure dynamics, spatial patterns, landslide numbers and volumes, we employed a physically based "Catchment-scale Hydromechanical Landslide Triggering" (CHLT) model for a study area where a summer storm in 2002 triggered 51 shallow landslides. In numerical experiments based on the CHLT model, we applied the measured rainfall amount of 53 mm in different artificial spatiotemporal rainfall patterns, resulting in between 30 and 100 landslides and total released soil volumes between 3000 and 60,000 m3 for the various scenarios. Results indicate that low intensity rainfall below soil's infiltration capacity resulted in the largest mechanical perturbation. This study illustrates how small-scale rainfall variability that is often overlooked by present operational rainfall data may play a key role in shaping landslide patterns.

Multiscaling properties of tropical rainfall: Analysis of rain gauge datasets in Lesser Antilles island environment

NASA Astrophysics Data System (ADS)

Bernard, Didier C.; Pasquier, Raphaël; Cécé, Raphaël; Dorville, Jean-François

2014-05-01

Changes in rainfall seem to be the main impact of climate change in the Caribbean area. The last conclusions of IPCC (2013), indicate that the end of this century will be marked by a rise of extreme rainfalls in tropical areas, linked with increase of the mean surface temperature. Moreover, most of the Lesser Antilles islands are characterized by a complex topography which tends to enhance the rainfall from synoptic disturbances by orographic effects. In the past five years, out of hurricanes passage, several extreme rainy events (approx. 16 mm in 6 minutes), including fatal cases, occurred in the Lesser Antilles Arc: in Guadeloupe (January 2011, May 2012 and 2013), in Martinique (May 2009, April 2011 and 2013), in Saint-Lucia (December 2013). These phenomena inducing floods, loss of life and material damages (agriculture sector and public infrastructures), inhibit the development of the islands. At this time, numerical weather prediction models as WRF, which are based on the equations of the atmospheric physics, do not show great results in the focused area (Bernard et al., 2013). Statistical methods may be used to examine explicitly local rainy updrafts, thermally and orographically induced at micro-scale. The main goal of the present insular tropical study is to characterize the multifractal symmetries occurring in the 6-min rainfall time series, registered since 2006 by the French Met. Office network weather stations. The universal multifractal model (Schertzer and Lovejoy, 1991) is used to define the statistical properties of measured rainfalls at meso-scale and micro-scale. This model is parametrized by a fundamental exponents set (H,a,C1,q) which are determined and compared with values found in the literature. The first three parameters characterize the mean pattern and the last parameter q, the extreme pattern. The occurrence ranges of multifractal regime are examined. The suggested links between the internal variability of the tropical rainy events and the multifractal properties found, are preliminary discussed. References Bernard, D., R. Cécé and J.-F. Dorville (2013). High resolution numerical simulation (WRF V3) of an extrem rainy event over the Guadeloupe archipelago: Case of 3-5 January 2011. EGU General Assembly 2013, Geophysical Research Abstracts, Vol. 15, EGU2013-9988, Vienna, April 2013. Schertzer, D., S. Lovejoy (1991). Nonlinear geodynamical variability: Multiple singularities, universality and observables. Scaling, fractals and non-linear variability in geophysics, D. Schertzer, S. Lovejoy eds.,41-82, Kluwer.

Simulated convective systems using a cloud resolving model: Impact of large-scale temperature and moisture forcing using observations and GEOS-3 reanalysis

NASA Technical Reports Server (NTRS)

Shie, C.-L.; Tao, W.-K.; Hou, A.; Lin, X.

2006-01-01

The GCE (Goddard Cumulus Ensemble) model, which has been developed and improved at NASA Goddard Space Flight Center over the past two decades, is considered as one of the finer and state-of-the-art CRMs (Cloud Resolving Models) in the research community. As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, GCE has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability. By basically using the large-scale temperature and moisture advective forcing, as well as the temperature, water vapor and wind fields obtained from TRMM (Tropical Rainfall Measuring Mission) field experiments such as SCSMEX (South China Sea Monsoon Experiment) and KWAJEX (Kwajalein Experiment), our recent 2-D and 3-D GCE simulations were able to capture detailed convective systems typical of the targeted (simulated) regions. The GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis data have also been proposed and successfully implemented for usage in the proposed/performed GCE long-term simulations (i.e., aiming at producing massive simulated cloud data -- Cloud Library) in compensating the scarcity of real field experimental data in both time and space (location). Preliminary 2-D or 3-D pilot results using GEOS-3 data have generally showed good qualitative agreement (yet some quantitative difference) with the respective numerical results using the SCSMEX observations. The first objective of this paper is to ensure the GEOS-3 data quality by comparing the model results obtained from several pairs of simulations using the real observations and GEOS-3 reanalysis data. The different large-scale advective forcing obtained from these two kinds of resources (i.e., sounding observations and GEOS-3 reanalysis) has been considered as a major critical factor in producing various model results. The second objective of this paper is therefore to investigate and present such an impact of large-scale forcing on various modeled quantities (such as hydrometeors, rainfall, and etc.). A third objective is to validate the overall GCE 3-D model performance by comparing the numerical results with sounding observations, as well as available satellite retrievals.

A protocol for conducting rainfall simulation to study soil runoff.

PubMed

Kibet, Leonard C; Saporito, Louis S; Allen, Arthur L; May, Eric B; Kleinman, Peter J A; Hashem, Fawzy M; Bryant, Ray B

2014-04-03

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff.

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

PubMed Central

Kibet, Leonard C.; Saporito, Louis S.; Allen, Arthur L.; May, Eric B.; Kleinman, Peter J. A.; Hashem, Fawzy M.; Bryant, Ray B.

2014-01-01

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff. PMID:24748061

Do we really use rainfall observations consistent with reality in hydrological modelling?

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

Evolution of Mesoscale Convective System over the South Western Peninsular India: Observations from Microwave Radiometer and Simulations using WRF

NASA Astrophysics Data System (ADS)

Uma, K. N.; Krishna Moorthy, K.; Sijikumar, S.; Renju, R.; Tinu, K. A.; Raju, Suresh C.

2012-07-01

Meso-scale Convective Systems (MCS) are important in view of their large cumulous build-up, vertical extent, short horizontal extent and associated thundershowers. The Microwave Radiometer Profiler (MRP) over the equatorial coastal station Thiruvanathapuram (Trivandrum, 8.55oN, 76.9oE), has been utilized to understand the genesis of Mesoscale convective system (MCS), that occur frequently during the pre-monsoon season. Examination of the measurement of relative humidity, temperature and cloud liquid water measurements, over the zenith and two scanning elevation angles (15o) viewing both over the land and the sea respectively revealed that the MCS generally originate over the land during early afternoon hours, propagate seawards over the observational site and finally dissipate over the sea, with accompanying rainfall and latent heat release. The simulations obtained using Advanced Research-Weather Research and Forecast (WRF-ARW) model effectively reproduces the thermodynamical and microphysical properties of the MCS. The time duration and quantity of rainfall obtained by the simulations also well compared with the observations. Analysis also suggests that wind shear in the upper troposphere is responsible for the growth and the shape of the convective cloud.

Simulated hydroclimatic impacts of projected Brazilian sugarcane expansion

NASA Astrophysics Data System (ADS)

Georgescu, M.; Lobell, D. B.; Field, C. B.; Mahalov, A.

2013-03-01

Sugarcane area is currently expanding in Brazil, largely in response to domestic and international demand for sugar-based ethanol. To investigate the potential hydroclimatic impacts of future expansion, a regional climate model is used to simulate 5 years of a scenario in which cerrado and cropland areas (~1.1E6 km2) within south-central Brazil are converted to sugarcane. Results indicate a cooling of up to ~1.0°C during the peak of the growing season, mainly as a result of increased albedo of sugarcane relative to the previous landscape. After harvest, warming of similar magnitude occurs from a significant decline in evapotranspiration and a repartitioning toward greater sensible heating. Overall, annual temperature changes from large-scale conversion are expected to be small because of offsetting reductions in net radiation absorption and evapotranspiration. The decline in net water flux from land to the atmosphere implies a reduction in regional precipitation, which is consistent with progressively decreasing simulated average rainfall for the study period, upon conversion to sugarcane. However, rainfall changes were not robust across three ensemble members. The results suggest that sugarcane expansion will not drastically alter the regional energy or water balance, but could result in important local and seasonal effects.

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2018-01-01

Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

Rainfall simulation experiments and Water Drop Penetration Time measurements shed light on the impact of water repellency on soils under organic farming management in Eastern Spain

NASA Astrophysics Data System (ADS)

Cerdà, Artemi; González, Óscar; León, Javier; Jordán, Antonio

2015-04-01

Water repellency is a well-know soil property since the research of professor Stefan Helmut Doerr recovered and powered the research developed by professor DeBano (Atanassova and Doerr, 2011; ; Jordán et al., 2011; Bodí et al., 2012; González Peñaloza et al., 2012 Bodí et al., 2013; García Moreno et al., 2013; Jordán et al., 2013; Badía-Villas et al., 2014; Jordán et al., 2013; Jiménez Morillo et al., 2015). However, little is known about the impact of water repellency in surface runoff generation, although usually is accepted that when more soil water repellent is a soil, higher will be the surface runoff discharge (Stoff et al., 2011; Madsen et al., 2011; León et al., 2013; Lozano et al., 2013; Mataix-Solera et al., 2013; Santos et al., 2015). And the impact of the water repellency and then the higher surface wash discharge can trigger high erosion rates (Kröpfl et al., 2013; Mandal and Sharda 2013; Zhao et al., 2013). However these relationships were not demonstrated as the most water repellent soils are the one with high organic contents, and those soils do not have soil losses, probably due to the high infiltration rates due to the macropore flow. Rainfall simulation experiments can shed light in the runoff generation mechanism as they can control the rainfall intensity (Bodí et al., 2012; Iserloh et al., 2012; Iserloh et al., 2013), and inform about the main mechanism of the soil erosion process Cerdà and Jurgensen, 2011; Daugherty et al., 2011; Podwojewski et al., 2011; Dunkerley, 2012; Garel et al., 2012; Jouquet et al., 2012; Kibet et al., 2013; Butzen et al., 2014; Ma et al., 2014; Martínez Murillo et al., 2013). To determine the relationship between surface runoff generated under simulated rainfall (Cerdà, 1988a; 1988b; Cerdà et al., 1998; Ziadat and Taimeh, 2013) with a small rainfall simulator (0.25 m2) and water repellency measurements with the Water Drop Penetration time methods were done (Bodí et al., 2012). The results show that the most water repellent soils generate a fast surface runoff that use to be infiltrate in macropores (cracks and fauna) and that runoff at plot scales was negligible in water repellent soils. Acknowledgements The research projects GL2008-02879/BTE, LEDDRA 243857 and PREVENTING AND REMEDIATING DEGRADATION OF SOILS IN EUROPE THROUGH LAND CARE (RECARE)FP7-ENV-2013- supported this research. References Atanassova, I., Doerr, S. H. 2011. Changes in soil organic compound composition associated with heat-induced increases in soil water repellency. European Journal of Soil Science, 62(4), 516-532. Badía-Villas, D., González-Pérez, J. A., Aznar, J. M., Arjona-Gracia, B., & Martí-Dalmau, C. 2014. Changes in water repellency, aggregation and organic matter of a mollic horizon burned in laboratory: soil depth affected by fire. Geoderma, 213, 400-407. Bodí, M. B., Doerr, S. H., Cerdà, A., Mataix-Solera, J. 2012. Hydrological effects of a layer of vegetation ash on underlying wettable and water repellent soil. Geoderma, 191, 14-23. Bodí, M.B. Doerr, S.H., Cerdà, A., Mataix-Solera, J. 2012. Hydrological effects of a layer of vegetation ash on underlying wettable and water repellent soils. Geoderma, 191, 14-23. http://dx.doi.org/10.1016/j.geoderma.2012.01.006 Bodí, M.B., Muñoz-Santa, I., Armero, C., Doerr, S.H., Mataix-Solera, J., Cerdà, A. 2013. Spatial and temporal variations of water repellency and probability of its occurrence in calcareous Mediterranean rangeland soils affected by fires. Catena, 108, 14-24. http://dx.doi.org/10.1016/j.catena.2012.04.002 Butzen, V., Seeger, M., Wirtz, S., Huemann, M., Mueller, C., Casper, M., Ries, J. B. 2014. Quantification of Hortonian overland flow generation and soil erosion in a Central European low mountain range using rainfall experiments. Catena, 113, 202-212. Cerdà, A. 1998a. Effect of climate on surface flow along a climatological gradient in Israel. A field rainfall simulation approach. Journal of Arid Environments, 38, 145-159. Cerdà, A. 1998b. The influence of aspect and vegetation on seasonal changes in erosion under rainfall simulation on a clay soil in Spain. Canadian Journal of Soil Science, 78, 321-330. Cerdà, A., Jurgensen, M. F. 2011. Ant mounds as a source of sediment on citrus orchard plantations in eastern Spain. A three-scale rainfall simulation approach. Catena, 85(3), 231-236. Dougherty, W. J., Mason, S. D., Burkitt, L. L., Milham, P. J. 2011. Relationship between phosphorus concentration in surface runoff and a novel soil phosphorus test procedure (DGT) under simulated rainfall. Soil Research, 49(6), 523-528. Dunkerley, D. 2012. Effects of rainfall intensity fluctuations on infiltration and runoff: rainfall simulation on dryland soils, Fowlers Gap, Australia. Hydrological Processes, 26(15), 2211-2224. García-Moreno, J., Gordillo-Rivero, Á. J., Zavala, L. M., Jordán, A., & Pereira, P. 2013. Mulch application in fruit orchards increases the persistence of soil water repellency during a 15-years period. Soil and Tillage Research, 130, 62-68. Garel, E., Marc, V., Ruy, S., Cognard-Plancq, A. L., Klotz, S., Emblanch, C., Simler, R. 2012. Large scale rainfall simulation to investigate infiltration processes in a small landslide under dry initial conditions: the Draix hillslope experiment. Hydrological Processes, 26(14), 2171-2186. González-Peñaloza, F.A., Cerdà, A., Zavala, L.M., Jordán, A., Giménez-Morera, A., Arcenegui, V. 2012. Do conservative agriculture practices increase soil water repellency? A case study in citrus-cropped soils. Soil and Tillage Research, 124, 233-239. http://dx.doi.org/10.1016/j.still.2012.06.015 Granged, A. J., Jordán, A., Zavala, L. M., Bárcenas, G. (2011): Fire-induced changes in soil water repellency increased fingered flow and runoff rates following the 2004 Huelva wildfire. Hydrological Processes, 25: 1614-1629. Iserloh, T., Ries, J.B., Arnaez, J., Boix Fayos, C., Butzen, V., Cerdà, A., Echeverría, M.T., Fernández-Gálvez, J., Fister, W., Geißler, C., Gómez, J.A., Gómez-Macpherson, H., Kuhn, N.J., Lázaro, R., León, F.J., Martínez-Mena, M., Martínez-Murillo, J.F., Marzen, M., Mingorance, M.D., Ortigosa, L., Peters, P., Regüés, D., Ruiz-Sinoga, J.D., Scholten, T., Seeger, M., Solé-Benet, A., Wengel, R., Wirtz, S. 2013. European small portable rainfall simulators: a comparison of rainfall characteristics. Catena, 110, 100-112. Doi: 10.1016/j.catena.2013.05.013 Iserloh, T., Ries, J.B., Cerdà, A., Echeverría, M.T., Fister, W., Geißler, C., Kuhn, N.J., León, F.J., Peters, P., Schindewolf, M., Schmidt, J., Scholten, T., Seeger, M. (2012): Comparative measurements with seven rainfall simulators on uniform bare fallow land. Zeitschrift für Geomorphologie, 57, 193-201. DOI: 10.1127/0372-8854/2012/S-00118. Jiménez-Morillo, N. T., González-Pérez, J. A., Jordán, A., Zavala, L. M., Rosa, J. M., Jiménez-González, M. A., & González-Vila, F. J. (2014). Organic matter fractions controlling soil water repellency in Sandy soils from the Doñana National Park (Southwestern Spain). Land Degradation & Development.| DOI: 10.1002/ldr.2314 Jordán, A., García-Moreno, J., Gordillo-Rivero, Á. J., Zavala, L. M., Cerdà, A. 2014. Organic carbon, water repellency and soil stability to slaking under different crops and managements: a case study at aggregate and intra-aggregate scales. SOIL Discussions, 1(1), 295-325. Jordán, A., Zavala, L. M., Mataix-Solera, J., Doerr, S. H. 2013. Soil water repellency: origin, assessment and geomorphological consequences. Catena, 108, 1-5. Jordán, A., Zavala, L. M., Mataix-Solera, J., Nava, A. L., & Alanís, N. 2011. Effect of fire severity on water repellency and aggregate stability on Mexican volcanic soils. Catena, 84(3), 136-147. Jouquet, P., Janeau, J. L., Pisano, A., Sy, H. T., Orange, D., Minh, L. T. N., Valentin, C. 2012. Influence of earthworms and termites on runoff and erosion in a tropical steep slope fallow in Vietnam: A rainfall simulation experiment. Applied Soil Ecology, 61, 161-168. Kibet, L. C., Saporito, L. S., Allen, A. L., May, E. B., Kleinman, P. J., Hashem, F. M., Bryant, R. B. 2013. A protocol for conducting rainfall simulation to study soil runoff. Journal of visualized experiments: JoVE, (86). Kröpfl, A. I., Cecchi, G. A., Villasuso, N. M., Distel, R. A. 2013. Degradation and recovery processes in Semi-Arid patchy rangelands of northern Patagonia, Argentina. Land Degradation & Development, 24: 393- 399. DOI 10.1002/ldr.1145 Cerdà, A., Schnabel, S., Gómez-Amelia, D. & Ceballos, A. 1998. Soil hydrological Response under simulated rainfall in the Dehesa ecosystem, Extremadura, SW, Spain. Earth Surface Processes and Landforms, 23, 195- 209 León, J. Bodí, M.B., Cerdà, A., Badía, D. 2013. The contrasted response of ash to wetting. The effects of ash type, thickness and rainfall events. Geoderma, 209-210, 143-152. http://dx.doi.org/10.1016/j.geoderma.2012.01.006 Lozano, E., Jiménez-Pinilla, P., Mataix-Solera, J., Arcenegui, V., Bárcenas, G. M., González-Pérez, J. A., Mataix- Beneyto, J. 2013. Biological and chemical factors controlling the patchy distribution of soil water repellency among plant species in a Mediterranean semiarid forest. Geoderma, 207, 212-220. Ma, W., Li, Z., Ding, K., Huang, J., Nie, X., Zeng, G., Liu, G. (2014). Effect of soil erosion on dissolved organic carbon redistribution in subtropical red soil under rainfall simulation. Geomorphology, 226, 217-225. Madsen, M. D., Zvirzdin, D. L., Petersen, S. L., Hopkins, B. G., Roundy, B. A., Chandler, D. G. 2011. Soil water repellency within a burned piñon-juniper woodland: Spatial distribution, severity, and ecohydrologic implications. Soil Science Society of America Journal, 75(4), 1543-1553. Mandal, D., Sharda, V. N. Appraisal of soil erosion risk in the Eastern Himalayan region of India for soil conservation planning. Land Degradation & Development, 24: 430-437. 2013. DOI 10.1002/ldr.1139 Martínez-Murillo, J. F., Nadal-Romero, E., Regüés, D., Cerdà, A., Poesen, J. 2013. Soil erosion and hydrology of the western Mediterranean badlands throughout rainfall simulation experiments: A review. Catena, 106, 101-112. Mataix-Solera, J., Arcenegui, V., Tessler, N., Zornoza, R., Wittenberg, L., Martínez, C., Jordán, M. M. 2013. Soil properties as key factors controlling water repellency in fire-affected areas: evidences from burned sites in Spain and Israel. Catena, 108, 6-13. Podwojewski, P., Janeau, J. L., Grellier, S., Valentin, C., Lorentz, S., Chaplot, V. 2011. Influence of grass soil cover on water runoff and soil detachment under rainfall simulation in a sub-humid South African degraded rangeland. Earth Surface Processes and Landforms, 36(7), 911-922. Santos, J. M., Verheijen, F. G., Tavares Wahren, F., Wahren, A., Feger, K. H., Bernard-Jannin, L., Nunes, J. P. (2015). Soil water repellency dynamics in pine and eucalupt plantation in Portugal - a high- resolution series. Land Degradation & Development. DOI: 10.1002/ldr.2251 Stoof, C. R., Moore, D., Ritsema, C. J., Dekker, L. W. 2011. Natural and fire-induced soil water repellency in a Portuguese shrubland. Soil Science Society of America Journal, 75(6), 2283-2295. Zhao, G., Mu, X., Wen, Z., Wang, F., and Gao, P. 2013. Soil erosion, conservation, and Eco-environment changes in the Loess Plateau of China. Land Degradation & Development, 24: 499- 510. DOI 10.1002/ldr.2246 Ziadat, F. M., Taimeh, A. Y. 2013. Effect of rainfall intensity, slope and land use and antecedent soil moisture on soil erosion in an arid environment. Land Degradation & Development, 24: 582- 590. DOI 10.1002/ldr.2239

Simulation of extreme rainfall event of November 2009 over Jeddah, Saudi Arabia: the explicit role of topography and surface heating

NASA Astrophysics Data System (ADS)

Almazroui, Mansour; Raju, P. V. S.; Yusef, A.; Hussein, M. A. A.; Omar, M.

2018-04-01

In this paper, a nonhydrostatic Weather Research and Forecasting (WRF) model has been used to simulate the extreme precipitation event of 25 November 2009, over Jeddah, Saudi Arabia. The model is integrated in three nested (27, 9, and 3 km) domains with the initial and boundary forcing derived from the NCEP reanalysis datasets. As a control experiment, the model integrated for 48 h initiated at 0000 UTC on 24 November 2009. The simulated rainfall in the control experiment depicts in well agreement with Tropical Rainfall Measurement Mission rainfall estimates in terms of intensity as well as spatio-temporal distribution. Results indicate that a strong low-level (850 hPa) wind over Jeddah and surrounding regions enhanced the moisture and temperature gradient and created a conditionally unstable atmosphere that favored the development of the mesoscale system. The influences of topography and heat exchange process in the atmosphere were investigated on the development of extreme precipitation event; two sensitivity experiments are carried out: one without topography and another without exchange of surface heating to the atmosphere. The results depict that both surface heating and topography played crucial role in determining the spatial distribution and intensity of the extreme rainfall over Jeddah. The topography favored enhanced uplift motion that further strengthened the low-level jet and hence the rainfall over Jeddah and adjacent areas. On the other hand, the absence of surface heating considerably reduced the simulated rainfall by 30% as compared to the observations.

Convection anomalies associated with warm eddy at the coastal area

NASA Astrophysics Data System (ADS)

Shi, R.; Wang, D.

2017-12-01

A possible correlation between a warm eddy and thunderstorms and convective precipitations are investigated at the coastal area in the northwestern South China Sea. Compared to the climatological mean in August from 2006 to 2013, an extreme enhancement of thunderstorm activities and precipitation rate are identified at the southern offshore area of Hainan island in August 2010 when a strong and long-live warm eddy was observed near the coastline at the same time. The 3 hourly satellite data (TRMM) indicate that the nocturnal convections is strong offshore and that could be responsible for the extreme positive anomalies of thunderstorms and rainfall in August 2010. The TRMM data also show a small reduction of thunderstorm activities and rainfall on the island in the afternoon. Meanwhile, the Weather Research and Forecasting (WRF) model was applied to simulate the change of rainfall in August 2010. The WRF simulation of rainfall rate is comparable with the observation results while there is some difference in the spatial distribution. The WRF simulation successfully captured the strong offshore rainfall and the diurnal variation of rainfall in August 2010. The WRF simulation indicated that the different convergence induced by sea/land breeze could be one essential reason for the adjustment of thunderstorms and rainfall in 2010. The substantial connection between sea/land breeze and upper layer heat content modified by the warm eddy is still on ongoing and will be reported in the future work.

Simulation of nitrous oxide and nitric oxide emissions from tropical primary forests in the Costa Rican Atlantic Zone

USGS Publications Warehouse

Liu, Shu-Guang; Reiners, William A.; Keller, Michael; Schimel, Davis S.

2000-01-01

WFPS is the dominant determinant of the fraction of gross N mineralization that is emitted from the soil as N2O and NO. If WFPS were not limiting during part of the year, this fraction would be 4.2%. With some periods of lower WFPS, the realized fraction is 2.2%. Because of the strong relationships between N2O and NO emission rates and rainfall and its derivative, WFPS, these moisture variables can be used to scale up nitrogen trace gas fluxes from sites to larger spatial scales.

Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability

NASA Astrophysics Data System (ADS)

Papoulakos, Konstantinos; Pollakis, Giorgos; Moustakis, Yiannis; Markopoulos, Apostolis; Iliopoulou, Theano; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris; Efstratiadis, Andreas

2017-04-01

Small islands are regarded as promising areas for developing hybrid water-energy systems that combine multiple sources of renewable energy with pumped-storage facilities. Essential element of such systems is the water storage component (reservoir), which implements both flow and energy regulations. Apparently, the representation of the overall water-energy management problem requires the simulation of the operation of the reservoir system, which in turn requires a faithful estimation of water inflows and demands of water and energy. Yet, in small-scale reservoir systems, this task in far from straightforward, since both the availability and accuracy of associated information is generally very poor. For, in contrast to large-scale reservoir systems, for which it is quite easy to find systematic and reliable hydrological data, in the case of small systems such data may be minor or even totally missing. The stochastic approach is the unique means to account for input data uncertainties within the combined water-energy management problem. Using as example the Livadi reservoir, which is the pumped storage component of the small Aegean island of Astypalaia, Greece, we provide a simulation framework, comprising: (a) a stochastic model for generating synthetic rainfall and temperature time series; (b) a stochastic rainfall-runoff model, whose parameters cannot be inferred through calibration and, thus, they are represented as correlated random variables; (c) a stochastic model for estimating water supply and irrigation demands, based on simulated temperature and soil moisture, and (d) a daily operation model of the reservoir system, providing stochastic forecasts of water and energy outflows. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Integrating remotely sensed surface water extent into continental scale hydrology

NASA Astrophysics Data System (ADS)

Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad

2016-12-01

In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R2, RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that remotely sensed surface water extent holds potential for improving rainfall-runoff streamflow simulations, potentially leading to a better forecast of the peak flow.

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

DOE PAGES

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; ...

2017-02-03

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are alreadymore » limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.« less

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are alreadymore » limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.« less

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

NASA Astrophysics Data System (ADS)

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; Hulshof, Catherine; Medvigy, David; Pizano, Camila; Salgado-Negret, Beatriz; Smith, Christina M.; Trierweiler, Annette; Van Bloem, Skip J.; Waring, Bonnie G.; Xu, Xiangtao; Powers, Jennifer S.

2017-02-01

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are already limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.

Which resilience of the continental rainfall-runoff chain?

NASA Astrophysics Data System (ADS)

Fraedrich, Klaus

2015-04-01

Processes along the continental rainfall-runoff chain are extremely variable over a wide range of time and space scales. A key societal question is the multiscale resilience of this chain. We argue that the adequate framework to tackle this question can be obtained by combining observations (ranging from minutes to decades) and minimalist concepts: (i) Rainfall exhibits 1/f-spectra if presented as binary events (tropics) and extrema world wide increase with duration according to Jennings' scaling law as simulated by a censored first-order autoregressive process representing vertical moisture fluxes. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function (Gumbel) not unlike physical systems at criticality, while short and long return times of extremes are Weibull-distributed. (iii) Soil moisture, interpreted by a biased coinflip Ansatz for rainfall events, provides an equation of state to the surface energy and water flux balances comprising Budyko's framework for quasi-stationary watershed analysis. (iv) Vegetation-greenness (NDVI), included as an active tracer extends Budyko's eco-hydrologic state space analysis, supplements the common geographical presentations, and it may be linked to a minimalist biodiversity concept. (v) Finally, attributions of change to external (or climate) and internal (or anthropogenic) causes are determined by eco-hydrologic state space trajectories using surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation). Risk-estimates (by GCM-emulators) and possible policy advice mechanisms enter the outlook.

Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

NASA Astrophysics Data System (ADS)

Cannon, Alex

2017-04-01

Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a univariate technique, and cannot incorporate information from additional covariates, for example ENSO state or physiographic controls on extreme rainfall within a region. Here, the univariate MQR model is extended to allow the use of multiple covariates. Multivariate monotone quantile regression (MMQR) is based on a single hidden-layer feedforward network with the quantile regression error function and partial monotonicity constraints. The MMQR model is demonstrated via Monte Carlo simulations and the estimation and visualization of regional trends in moderate rainfall extremes based on homogenized sub-daily precipitation data at stations in Canada.

Accessing the capability of TRMM 3B42 V7 to simulate streamflow during extreme rain events: Case study for a Himalayan River Basin

NASA Astrophysics Data System (ADS)

Kumar, Brijesh; Lakshmi, Venkat

2018-03-01

The paper examines the quality of Tropical Rainfall Monitoring Mission (TRMM) 3B42 V7 precipitation product to simulate the streamflow using Soil Water Assessment Tool (SWAT) model for various rainfall intensities over the Himalayan region. The SWAT model has been set up for Gandak River Basin with 41 sub-basins and 420 HRUs. Five stream gauge locations are used to simulate the streamflow for a time span of 10 years (2000-2010). Daily streamflow for the simulation period is collected from Central Water Commission (CWC), India and Department of Hydrology and Meteorology (DHM), Nepal. The simulation results are found good in terms of Nash-Sutcliffe efficiency (NSE) {>}0.65, coefficient of determination (R2) {>}0.67 and Percentage Bias (PBIAS){<}15%, at each stream gauge sites. Thereafter, we have calculated the PBIAS and RMSE-observations standard deviation ratio (RSR) statistics between TRMM simulated and observed streamflow for various rainfall intensity classes, viz., light ({<}7.5 mm/d), moderate (7.5 to 35.4 mm/d), heavy (35.5 to 124.4 mm/d) and extremely heavy ({>}124.4 mm/d). The PBIAS and RSR show that TRMM simulated streamflow is suitable for moderate to heavy rainfall intensities. However, it does not perform well for light- and extremely-heavy rainfall intensities. The finding of the present work is useful for the problems related to water resources management, irrigation planning and hazard analysis over the Himalayan regions.

Statistical evaluation of rainfall-simulator and erosion testing procedure : final report.

DOT National Transportation Integrated Search

1977-01-01

The specific aims of this study were (1) to supply documentation of statistical repeatability and precision of the rainfall-simulator and to document the statistical repeatabiity of the soil-loss data when using the previously recommended tentative l...

A simple lightning assimilation technique for improving ...

EPA Pesticide Factsheets

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly averaged bias of 6 h accumulated rainfall is reduced from 0.54 to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF applications. The

A Simple Lightning Assimilation Technique For Improving ...

EPA Pesticide Factsheets

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: Force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly-averaged bias of 6-h accumulated rainfall is reduced from 0.54 mm to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF appli

A Decade-long Continental-Scale Convection-Resolving Climate Simulation on GPUs

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Lapillonne, Xavier; Lüthi, Daniel; Schär, Christoph

2016-04-01

The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. Using horizontal grid spacings of O(1km), they allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer-designs that involve conventional multicore CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation using the GPU-enabled COSMO version. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss the performance of the convection-resolving modeling approach on the European scale. Specifically we focus on the annual cycle of convection in Europe, on the organization of convective clouds and on the verification of hourly rainfall with various high resolution datasets.

Regional rainfall-runoff relations for simulation of streamflow for watersheds in Du Page County, Illinois

USGS Publications Warehouse

Duncker, James J.; Melching, Charles S.

1998-01-01

Rainfall and streamflow data collected from July 1986 through September 1993 were utilized to calibrate and verify a continuous-simulation rainfall-runoff model for three watersheds (11.8--18.0 square miles in area) in Du Page County. Classification of land cover into three categories of pervious (grassland, forest/wetland, and agricultural land) and one category of impervious subareas was sufficient to accurately simulate the rainfall-runoff relations for the three watersheds. Regional parameter sets were obtained by calibrating jointly all parameters except fraction of ground-water inflow that goes to inactive ground water (DEEPFR), interflow recession constant (IRC), and infiltration (INFILT) for runoff from all three watersheds. DEEPFR and IRC varied among the watersheds because of physical differences among the watersheds. Two values of INFILT were obtained: one representing the rainfall-runoff process on the silty and clayey soils on the uplands and lake plains that characterize Sawmill Creek, St. Joseph Creek, and eastern Du Page County; and one representing the rainfall-runoff process on the silty soils on uplands that characterize Kress Creek and parts of western Du Page County. Regional rainfall-runoff relations, defined through joint calibration of the rainfall-runoff model and verified for independent periods, presented in this report, allow estimation of runoff for watersheds in Du Page County with an error in the total water balance less than 4.0 percent; an average absolute error in the annual-flow estimates of 17.1 percent with the error rarely exceeding 25 percent for annual flows; and correlation coefficients and coefficients of model-fit efficiency for monthly flows of at least 87 and 76 percent, respectively. Close reproduction of the runoff-volume duration curves was obtained. A frequency analysis of storm-runoff volume indicates a tendency of the model to undersimulate large storms, which may result from underestimation of the amount of impervious land cover in the watershed and errors in measuring rainfall for convective storms. Overall, the results of regional calibration and verification of the rainfall-runoff model indicate the simulated rainfall-runoff relations are adequate for stormwater-management planning and design for watersheds in Du Page County.

Validation and evaluation of epistemic uncertainty in rainfall thresholds for regional scale landslide forecasting

NASA Astrophysics Data System (ADS)

Gariano, Stefano Luigi; Brunetti, Maria Teresa; Iovine, Giulio; Melillo, Massimo; Peruccacci, Silvia; Terranova, Oreste Giuseppe; Vennari, Carmela; Guzzetti, Fausto

2015-04-01

Prediction of rainfall-induced landslides can rely on empirical rainfall thresholds. These are obtained from the analysis of past rainfall events that have (or have not) resulted in slope failures. Accurate prediction requires reliable thresholds, which need to be validated before their use in operational landslide warning systems. Despite the clear relevance of validation, only a few studies have addressed the problem, and have proposed and tested robust validation procedures. We propose a validation procedure that allows for the definition of optimal thresholds for early warning purposes. The validation is based on contingency table, skill scores, and receiver operating characteristic (ROC) analysis. To establish the optimal threshold, which maximizes the correct landslide predictions and minimizes the incorrect predictions, we propose an index that results from the linear combination of three weighted skill scores. Selection of the optimal threshold depends on the scope and the operational characteristics of the early warning system. The choice is made by selecting appropriately the weights, and by searching for the optimal (maximum) value of the index. We discuss weakness in the validation procedure caused by the inherent lack of information (epistemic uncertainty) on landslide occurrence typical of large study areas. When working at the regional scale, landslides may have occurred and may have not been reported. This results in biases and variations in the contingencies and the skill scores. We introduce two parameters to represent the unknown proportion of rainfall events (above and below the threshold) for which landslides occurred and went unreported. We show that even a very small underestimation in the number of landslides can result in a significant decrease in the performance of a threshold measured by the skill scores. We show that the variations in the skill scores are different for different uncertainty of events above or below the threshold. This has consequences in the ROC analysis. We applied the proposed procedure to a catalogue of rainfall conditions that have resulted in landslides, and to a set of rainfall events that - presumably - have not resulted in landslides, in Sicily, in the period 2002-2012. First, we determined regional event duration-cumulated event (ED) rainfall thresholds for shallow landslide occurrence using 200 rainfall conditions that have resulted in 223 shallow landslides in Sicily in the period 2002-2011. Next, we validated the thresholds using 29 rainfall conditions that have triggered 42 shallow landslides in Sicily in 2012, and 1250 rainfall events that presumably have not resulted in landslides in the same year. We performed a back analysis simulating the use of the thresholds in a hypothetical landslide warning system operating in 2012.

Impact of capturing rainfall scavenging intermittency using cloud superparameterization on simulated continental scale wildfire smoke transport

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Kooperman, G. J.; Zhao, Z.; Wang, M.; Russell, L. M.; Somerville, R. C.; Ghan, S. J.

2011-12-01

Evaluating the fidelity of new aerosol physics in climate models is confounded by uncertainties in source emissions, systematic error in cloud parameterizations, and inadequate sampling of long-range plume concentrations. To explore the degree to which cloud parameterizations distort aerosol processing and scavenging, the Pacific Northwest National Laboratory (PNNL) Aerosol-Enabled Multi-Scale Modeling Framework (AE-MMF), a superparameterized branch of the Community Atmosphere Model Version 5 (CAM5), is applied to represent the unusually active and well sampled North American wildfire season in 2004. In the AE-MMF approach, the evolution of double moment aerosols in the exterior global resolved scale is linked explicitly to convective statistics harvested from an interior cloud resolving scale. The model is configured in retroactive nudged mode to observationally constrain synoptic meteorology, and Arctic wildfire activity is prescribed at high space/time resolution using data from the Global Fire Emissions Database. Comparisons against standard CAM5 bracket the effect of superparameterization to isolate the role of capturing rainfall intermittency on the bulk characteristics of 2004 Arctic plume transport. Ground based lidar and in situ aircraft wildfire plume constraints from the International Consortium for Atmospheric Research on Transport and Transformation field campaign are used as a baseline for model evaluation.

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lau, W.; Baker, R.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo-China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the low-level temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation. The model results will be compared to the simulation of the 6-7 May 2000 Missouri flash flood event. In addition, the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation will be examined.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Lau, W.; Baker, R. D.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo-China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the low-level temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation. The model results will be compared to the simulation of the 6-7 May 2000 Missouri flash flood event. In addition, the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation will be examined.

Estimation of small-scale soil erosion in laboratory experiments with Structure from Motion photogrammetry

NASA Astrophysics Data System (ADS)

Balaguer-Puig, Matilde; Marqués-Mateu, Ángel; Lerma, José Luis; Ibáñez-Asensio, Sara

2017-10-01

The quantitative estimation of changes in terrain surfaces caused by water erosion can be carried out from precise descriptions of surfaces given by means of digital elevation models (DEMs). Some stages of water erosion research efforts are conducted in the laboratory using rainfall simulators and soil boxes with areas less than 1 m2. Under these conditions, erosive processes can lead to very small surface variations and high precision DEMs are needed to account for differences measured in millimetres. In this paper, we used a photogrammetric Structure from Motion (SfM) technique to build DEMs of a 0.5 m2 soil box to monitor several simulated rainfall episodes in the laboratory. The technique of DEM of difference (DoD) was then applied using GIS tools to compute estimates of volumetric changes between each pair of rainfall episodes. The aim was to classify the soil surface into three classes: erosion areas, deposition areas, and unchanged or neutral areas, and quantify the volume of soil that was eroded and deposited. We used a thresholding criterion of changes based on the estimated error of the difference of DEMs, which in turn was obtained from the root mean square error of the individual DEMs. Experimental tests showed that the choice of different threshold values in the DoD can lead to volume differences as large as 60% when compared to the direct volumetric difference. It turns out that the choice of that threshold was a key point in this method. In parallel to photogrammetric work, we collected sediments from each rain episode and obtained a series of corresponding measured sediment yields. The comparison between computed and measured sediment yields was significantly correlated, especially when considering the accumulated value of the five simulations. The computed sediment yield was 13% greater than the measured sediment yield. The procedure presented in this paper proved to be suitable for the determination of sediment yields in rainfall-driven soil erosion experiments conducted in the laboratory.

A systematic assessment of watershed-scale nonpoint source pollution during rainfall-runoff events in the Miyun Reservoir watershed.

PubMed

Qiu, Jiali; Shen, Zhenyao; Wei, Guoyuan; Wang, Guobo; Xie, Hui; Lv, Guanping

2018-03-01

The assessment of peak flow rate, total runoff volume, and pollutant loads during rainfall process are very important for the watershed management and the ecological restoration of aquatic environment. Real-time measurements of rainfall-runoff and pollutant loads are always the most reliable approach but are difficult to carry out at all desired location in the watersheds considering the large consumption of material and financial resources. An integrated environmental modeling approach for the estimation of flash streamflow that combines the various hydrological and quality processes during rainstorms within the agricultural watersheds is essential to develop targeted management strategies for the endangered drinking water. This study applied the Hydrological Simulation Program-Fortran (HSPF) to simulate the spatial and temporal variation in hydrological processes and pollutant transport processes during rainstorm events in the Miyun Reservoir watershed, a drinking water resource area in Beijing. The model performance indicators ensured the acceptable applicability of the HSPF model to simulate flow and pollutant loads in the studied watershed and to establish a relationship between land use and the parameter values. The proportion of soil and land use was then identified as the influencing factors of the pollution intensities. The results indicated that the flush concentrations were much higher than those observed during normal flow periods and considerably exceeded the limits of Class III Environmental Quality Standards for Surface Water (GB3838-2002) for the secondary protection zones of the drinking water resource in China. Agricultural land and leached cinnamon soils were identified as the key sources of sediment, nutrients, and fecal coliforms. Precipitation volume was identified as a driving factor that determined the amount of runoff and pollutant loads during rainfall processes. These results are useful to improve the streamflow predictions, provide useful information for the identification of highly polluted areas, and aid the development of integrated watershed management system in the drinking water resource area.

Indices of climate change based on patterns from CMIP5 models, and the range of projections

NASA Astrophysics Data System (ADS)

Watterson, I. G.

2018-05-01

Changes in temperature, precipitation, and other variables simulated by 40 current climate models for the 21st century are approximated as the product of the global mean warming and a spatial pattern of scaled changes. These fields of standardized change contain consistent features of simulated change, such as larger warming over land and increased high-latitude precipitation. However, they also differ across the ensemble, with standard deviations exceeding 0.2 for temperature over most continents, and 6% per degree for tropical precipitation. These variations are found to correlate, often strongly, with indices based on those of modes of interannual variability. Annular mode indices correlate, across the 40 models, with regional pressure changes and seasonal rainfall changes, particularly in South America and Europe. Equatorial ocean warming rates link to widespread anomalies, similarly to ENSO. A Pacific-Indian Dipole (PID) index representing the gradient in warming across the maritime continent is correlated with Australian rainfall with coefficient r of - 0.8. The component of equatorial warming orthogonal to this index, denoted EQN, has strong links to temperature and rainfall in Africa and the Americas. It is proposed that these indices and their associated patterns might be termed "modes of climate change". This is supported by an analysis of empirical orthogonal functions for the ensemble of standardized fields. Can such indices be used to help constrain projections? The relative similarity of the PID and EQN values of change, from models that have more skilful simulation of the present climate tropical pressure fields, provides a basis for this.

Vertical Motion Changes Related to North-East Brazil Rainfall Variability: a GCM Simulation

NASA Astrophysics Data System (ADS)

Roucou, Pascal; Oribe Rocha de Aragão, José; Harzallah, Ali; Fontaine, Bernard; Janicot, Serge

1996-08-01

The atmospheric structure over north-east Brazil during anomalous rainfall years is studied in the 11 levels of the outputs of the Laboratoire de Météorologie Dynamique atmospheric general circulation model (LMD AGCM). Seven 19-year simulations were performed using observed sea-surface temperature (SST) corresponding to the period 1970- 1988. The ensemble mean is calculated for each month of the period, leading to an ensemble-averaged simulation. The simulated March-April rainfall is in good agreement with observations. Correlations of simulated rainfall and three SST indices relative to the equatorial Pacific and northern and southern parts of the Atlantic Ocean exhibit stronger relationships in the simulation than in the observations. This is particularly true with the SST gradient in the Atlantic (Atlantic dipole). Analyses on 200 ;hPa velocity potential, vertical velocity, and vertical integral of the zonal component of mass flux are performed for years of abnormal rainfall and positive/negative SST anomalies in the Pacific and Atlantic oceans in March-April during the rainy season over the Nordeste region. The results at 200 hPa show a convergence anomaly over Nordeste and a divergence anomaly over the Pacific concomitant with dry seasons associated with warm SST anomalies in the Pacific and warm (cold) waters in the North (South) Atlantic. During drought years convection inside the ITCZ indicated by the vertical velocity exhibits a displacement of the convection zone corresponding to a northward migration of the ITCZ. The east-west circulation depicted by the zonal divergent mass flux shows subsiding motion over Nordeste and ascending motion over the Pacific in drought years, accompanied by warm waters in the eastern Pacific and warm/cold waters in northern/southern Atlantic. Rainfall variability of the Nordeste rainfall is linked mainly to vertical motion and SST variability through the migration of the ITCZ and the east-west circulation.

A novel approach to model dynamic flow interactions between storm sewer system and overland surface for different land covers in urban areas

NASA Astrophysics Data System (ADS)

Chang, Tsang-Jung; Wang, Chia-Ho; Chen, Albert S.

2015-05-01

In this study, we developed a novel approach to simulate dynamic flow interactions between storm sewers and overland surface for different land covers in urban areas. The proposed approach couples the one-dimensional (1D) sewer flow model (SFM) and the two-dimensional (2D) overland flow model (OFM) with different techniques depending on the land cover type of the study areas. For roads, pavements, plazas, and so forth where rainfall becomes surface runoff before entering the sewer system, the rainfall-runoff process is simulated directly in the 2D OFM, and the runoff is drained to the sewer network via inlets, which is regarded as the input to 1D SFM. For green areas on which rainfall falls into the permeable ground surface and the generated direct runoff traverses terrain, the deduction rate is applied to the rainfall for reflecting the soil infiltration in the 2D OFM. For flat building roofs with drainage facilities allowing rainfall to drain directly from the roof to sewer networks, the rainfall-runoff process is simulated using the hydrological module in the 1D SFM where no rainfall is applied to these areas in the 2D OFM. The 1D SFM is used for hydraulic simulations in the sewer network. Where the flow in the drainage network exceeds its capacity, a surcharge occurs and water may spill onto the ground surface if the pressure head in a manhole exceeds the ground elevation. The overflow discharge from the sewer system is calculated by the 1D SFM and considered a point source in the 2D OFM. The overland flow will return into the sewer network when it reaches an inlet that connects to an un-surcharged manhole. In this case, the inlet is considered as a point sink in the 2D OFM and an inflow to a manhole in the 1D SFM. The proposed approach was compared to other five urban flood modelling techniques with four rainfall events that had previously recorded inundation areas. The merits and drawbacks of each modelling technique were compared and discussed. Based on the simulated results, the proposed approach was found to simulate floodings closer to the survey records than other approaches because the physical rainfall-runoff phenomena in urban environment were better reflected.

Simulations for Making On-farm Decisions in Relation to ENSO in Semi-arid Areas, South Africa

NASA Astrophysics Data System (ADS)

Tesfuhuney, W. A.; Crespo, O. O.; Walker, S. S.; Steyn, S. A.

2017-12-01

The study was employed to investigate and improve on-farm decision making on planting dates and fertilization by relating simulated yield and seasonal outlook information. The Agricultural Production Systems SIMulator model (APSIM) was used to explore ENSO/SOI effects for small-scale farmers to represent weather conditions and soil forms of semi-arid areas of Bothaville, Bethlehem and Bloemfontein regions in South Africa. The relationships of rainfall and SOI anomalies indicate a positive correlation, signifies ENSO/SOI as seasonal outlooks for study areas. Model evaluation results showed higher degree of bias (RMSEs/RMSE value of 0.88-0.98). The D-index of agreement in the range 0.61-0.71 indicate the ability of the APSIM-Maize model is an adequate tool in evaluating relative changes in maize yield in relation to various management practices and seasonal variations. During rainy, La Niño years (SOI > +5), highest simulated yields were found for Bethlehem in November with addition of 100 - 150 kg ha-1 N fertilization and up to 50 kg ha-1 for both Bothaville and Bloemfontein. With respect to various levels of fertilization, the dry El Niño years (SOI < -5) had a range of 0.90-1.31, 3.03-3.54 and 1.11-1.26 t ha-1 yields and showed to increase during La Niña years with a range of 2.50-2.66, 3.36-4.79 and 2.24-2.38 t ha-1 at Bothaville, Bethlehem and Bloemfontein for November planting. During El Niño episodes planting earlier and using 50 kg ha-1 fertilizer with improved short maturing cultivar are effective adaptation measures to counteract poor soils and erratic rainfall of semi-arid environment, Under optimal soil conditions and/or when probability of La Niño episodes, optimal yields are obtained by maximizing fertilization. Effective rainfall and tactical on-farm management decisions in associate with seasonal rainfall out looks information is a useful mechanism in reducing risk for dryland farming in semi-arid regions. Key word: Semi-arid; APSIM; SOI; El Niño / La Niña; On-farm Decisions

Some Precipitation Studies over Andhra Pradesh and the Bay of Bengal using TRMM and SSMI data

NASA Astrophysics Data System (ADS)

Rao, S. Ramalingeswara; Krishna, K. Muni; Kumar, Bhanu

2007-07-01

One of the most difficult issues in modeling the global atmosphere and climate by General Circulation Models is the simulation and initialization of precipitation processes and at the same time rainfall is most important meteorological parameter that effects India's economy. An attempt is made in the present study to evaluate diurnal variation of rain rates over the Bay of Bengal (BoB) for the months June through December during 1999-2002. TMI rainfall product of Wentz and Spencer and SSMI data sets were used in this study. Mean hourly rain rates were calculated over the BoB (10°-15° N and 85°-95°E) and discussed; this study highlights that maximum rain rates are observed in the afternoons during summer monsoon seasons. Secondly mean monthly annual cycle of rainfall is prepared using 3B42RT merged rain product and compared with mean monthly India Meteorological Department (IMD) data for the study period over Andhra Pradesh (A.P). Time series of daily variations of 3B42RT precipitation and observed real time rainfall data over A.P. for the study period is validated and the relationship between them is statistically significant at 1% level. Similarly mean monthly data prepared from the daily analysis and compared with the IMD mean monthly rainfall maps. The comparison suggests that even with only available real time data from 3B42RT and rain gauge, it is possible to construct usable large-scale rainfall maps on regular latitude-longitude grids. This analysis, which uses a high resolution and more local rain gauge data, is able to produce realistic details of Indian summer monsoon rainfall over the study period.

Modelled rainfall skill assessment against a 1000-year time/space isotope dendro-climatology for southern Africa

NASA Astrophysics Data System (ADS)

Woodborne, Stephan; Hall, Grant; Zhang, Qiong

2016-04-01

Palaeoclimate reconstruction using isotopic analysis of tree growth increments has yielded a 1000-year record of rainfall variability in southern Africa. Isotope dendro-climatology reconstructions from baobab trees (Adansonia digitata) provide evidence for rainfall variability from the arid Namib Desert and the Limpopo River Valley. Isotopic analysis of a museum specimen of a yellowwood tree (Podocarps falcatus) yields another record from the southwestern part of the subcontinent. Combined with the limited classic denro-climatologies available in the region these records yield palaeo-rainfall variability in the summer and winter rainfall zones as well as the hyper-arid zone over the last 1000 years. Coherent shifts in all of the records indicate synoptic changes in the westerlies, the inter-tropical convergence zone, and the Congo air boundary. The most substantial rainfall shift takes place at about 1600 CE at the onset of the Little Ice Age. Another distinctive feature of the record is a widespread phenomenon that occurs shortly after 1810 CE that in southern Africa corresponds with a widespread social upheaval known as the Difequane or Mfekane. Large scale forcing of the system includes sea-surface temperatures in the Agulhas Current, the El Nino Southern Oscillation and the Southern Annular Mode. The Little Ice Age and Mfekane climate shifts result from different forcing mechanisms, and the rainfall response in the different regions at these times do not have a fixed phase relationship. This complexity provides a good scenario to test climate models. A first order (wetter versus drier) comparison between each of the tree records and a 1000-year palaeoclimate model simulation for the Little Ice Age and Mfekane transitions demonstrates a generally good correspondence.

Evaluating rainfall errors in global climate models through cloud regimes

NASA Astrophysics Data System (ADS)

Tan, Jackson; Oreopoulos, Lazaros; Jakob, Christian; Jin, Daeho

2017-07-01

Global climate models suffer from a persistent shortcoming in their simulation of rainfall by producing too much drizzle and too little intense rain. This erroneous distribution of rainfall is a result of deficiencies in the representation of underlying processes of rainfall formation. In the real world, clouds are precursors to rainfall and the distribution of clouds is intimately linked to the rainfall over the area. This study examines the model representation of tropical rainfall using the cloud regime concept. In observations, these cloud regimes are derived from cluster analysis of joint-histograms of cloud properties retrieved from passive satellite measurements. With the implementation of satellite simulators, comparable cloud regimes can be defined in models. This enables us to contrast the rainfall distributions of cloud regimes in 11 CMIP5 models to observations and decompose the rainfall errors by cloud regimes. Many models underestimate the rainfall from the organized convective cloud regime, which in observation provides half of the total rain in the tropics. Furthermore, these rainfall errors are relatively independent of the model's accuracy in representing this cloud regime. Error decomposition reveals that the biases are compensated in some models by a more frequent occurrence of the cloud regime and most models exhibit substantial cancellation of rainfall errors from different regimes and regions. Therefore, underlying relatively accurate total rainfall in models are significant cancellation of rainfall errors from different cloud types and regions. The fact that a good representation of clouds does not lead to appreciable improvement in rainfall suggests a certain disconnect in the cloud-precipitation processes of global climate models.

High resolution numerical simulation (WRF V3) of an extreme rainy event over the Guadeloupe archipelago: Case of 3-5 january 2011.

NASA Astrophysics Data System (ADS)

Bernard, Didier C.; Cécé, Raphaël; Dorville, Jean-François

2013-04-01

During the dry season, the Guadeloupe archipelago may be affected by extreme rainy disturbances which may induce floods in a very short time. C. Brévignon (2003) considered a heavy rain event for rainfall upper 100 mm per day (out of mountainous areas) for this tropical region. During a cold front passage (3-5 January 2011), torrential rainfalls caused floods, major damages, landslides and five deaths. This phenomenon has put into question the current warning system based on large scale numerical models. This low-resolution forecasting (around 50-km scale) has been unsuitable for small tropical island like Guadeloupe (1600 km2). The most affected area was the middle of Grande-Terre island which is the main flat island of the archipelago (area of 587 km2, peak at 136 m). It is the most populated sector of Guadeloupe. In this area, observed rainfall have reached to 100-160 mm in 24 hours (this amount is equivalent to two months of rain for January (C. Brévignon, 2003)), in less 2 hours drainage systems have been saturated, and five people died in a ravine. Since two years, the atmospheric model WRF ARW V3 (Skamarock et al., 2008) has been used to modeling meteorological variables fields observed over the Guadeloupe archipelago at high resolution 1-km scale (Cécé et al., 2011). The model error estimators show that meteorological variables seem to be properly simulated for standard types of weather: undisturbed, strong or weak trade winds. These simulations indicate that for synoptic winds weak to moderate, a small island like Grande-Terre is able to generate inland convergence zones during daytime. In this presentation, we apply this high resolution model to simulate this extreme rainy disturbance of 3-5 January 2011. The evolution of modeling meteorological variable fields is analyzed in the most affected area of Grande-Terre (city of Les Abymes). The main goal is to examine local quasi-stationary updraft systems and highlight their convective mechanisms. The spatio-temporal distribution of simulated rainfall could help to design the prevention and evacuation plan, particularly for the flooding areas. The meteorological variable fields simulated are evaluated by comparison with observed data of meteorological weather stations (French Met. Office) available in the area. Brévignon, C., 2003: Atlas climatique: l'environnement atmosphérique de la Guadeloupe, de Saint-Barthélémy et Saint-martin. Météo-France, Service Régional de Guadeloupe, 92 pp. Cécé, R., T. Plocoste, C. D'Alexis, D. Bernard and J.-F. Dorville, 2012: Modélisation numérique à l'échelle locale des situations météorologiques observées au cours de la transition saison sèche - saison humide à l'aide de WRF ARW V3 : cas de l'archipel de la Guadeloupe. AMA 2012, Toulouse. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers, 2008: A Description of the Advanced Research WRF Version 3.Tech. Rep., National Center for Atmospheric Research.

Modeling effectiveness of management practices for flood mitigation using GIS spatial analysis functions in Upper Cilliwung watershed

NASA Astrophysics Data System (ADS)

Darma Tarigan, Suria

2016-01-01

Flooding is caused by excessive rainfall flowing downstream as cumulative surface runoff. Flooding event is a result of complex interaction of natural system components such as rainfall events, land use, soil, topography and channel characteristics. Modeling flooding event as a result of interaction of those components is a central theme in watershed management. The model is usually used to test performance of various management practices in flood mitigation. There are various types of management practices for flood mitigation including vegetative and structural management practices. Existing hydrological model such as SWAT and HEC-HMS models have limitation to accommodate discrete management practices such as infiltration well, small farm reservoir, silt pits in its analysis due to the lumped structure of these models. Aim of this research is to use raster spatial analysis functions of Geo-Information System (RGIS-HM) to model flooding event in Ciliwung watershed and to simulate impact of discrete management practices on surface runoff reduction. The model was validated using flooding data event of Ciliwung watershed on 29 January 2004. The hourly hydrograph data and rainfall data were available during period of model validation. The model validation provided good result with Nash-Suthcliff efficiency of 0.8. We also compared the RGIS-HM with Netlogo Hydrological Model (NL-HM). The RGIS-HM has similar capability with NL-HM in simulating discrete management practices in watershed scale.

Changes in the Structure and Propagation of the MJO with Increasing CO2

NASA Technical Reports Server (NTRS)

Adames, Angel F.; Kim, Daehyun; Sobel, Adam H.; Del Genio, Anthony; Wu, Jingbo

2017-01-01

Changes in the Madden-Julian Oscillation (MJO) with increasing CO2 concentrations are examined using the Goddard Institute for Space Studies Global Climate Model (GCM). Four simulations performed with fixed CO2 concentrations of 0.5, 1, 2 and 4 times pre-industrial levels using the GCM coupled with a mixed layer ocean model are analyzed in terms of the basic state, rainfall and moisture variability, and the structure and propagation of the MJO.The GCM simulates basic state changes associated with increasing CO2 that are consistent with results from earlier studies: column water vapor increases at approximately 7.1% K(exp -1), precipitation also increases but at a lower rate (approximately 3% K(exp -1)), and column relative humidity shows little change. Moisture and rainfall variability intensify with warming. Total moisture and rainfall variability increases at a rate that is similar to that of the mean state change. The intensification is faster in the MJO-related anomalies than in the total anomalies, though the ratio of the MJO band variability to its westward counterpart increases at a much slower rate. On the basis of linear regression analysis and space-time spectral analysis, it is found that the MJO exhibits faster eastward propagation, faster westward energy dispersion, a larger zonal scale and deeper vertical structure in warmer climates.

Short-term rainfall: its scaling properties over Portugal

NASA Astrophysics Data System (ADS)

de Lima, M. Isabel P.

2010-05-01

The characterization of rainfall at a variety of space- and time-scales demands usually that data from different origins and resolution are explored. Different tools and methodologies can be used for this purpose. In regions where the spatial variation of rain is marked, the study of the scaling structure of rainfall can lead to a better understanding of the type of events affecting that specific area, which is essential for many engineering applications. The relevant factors affecting rain variability, in time and space, can lead to contrasting statistics which should be carefully taken into account in design procedures and decision making processes. One such region is Mainland Portugal; the territory is located in the transitional region between the sub-tropical anticyclone and the subpolar depression zones and is characterized by strong north-south and east-west rainfall gradients. The spatial distribution and seasonal variability of rain are particularly influenced by the characteristics of the global circulation. One specific feature is the Atlantic origin of many synoptic disturbances in the context of the regional geography (e.g. latitude, orography, oceanic and continental influences). Thus, aiming at investigating the statistical signature of rain events of different origins, resulting from the large number of mechanisms and factors affecting the rainfall climate over Portugal, scale-invariant analyses of the temporal structure of rain from several locations in mainland Portugal were conducted. The study used short-term rainfall time series. Relevant scaling ranges were identified and characterized that help clarifying the small-scale behaviour and statistics of this process.

Commercial application of rainfall simulation

NASA Astrophysics Data System (ADS)

Loch, Rob J.

2010-05-01

Landloch Pty Ltd is a commercial consulting firm, providing advice on a range of land management issues to the mining and construction industries in Australia. As part of the company's day-to-day operations, rainfall simulation is used to assess material erodibility and to investigate a range of site attributes. (Landloch does carry out research projects, though such are not its core business.) When treated as an everyday working tool, several aspects of rainfall simulation practice are distinctively modified. Firstly, the equipment used is regularly maintained, and regularly upgraded with a primary focus on ease, safety, and efficiency of use and on reliability of function. As well, trained and experienced technical support is considered essential. Landloch's chief technician has over 10 years experience in running rainfall simulators at locations across Australia and in Africa and the Pacific. Secondly, the specific experimental conditions established for each set of rainfall simulator runs are carefully considered to ensure that they accurately represent the field conditions to which the data will be subsequently applied. Considerations here include: • wetting and drying cycles to ensure material consolidation and/or cementation if appropriate; • careful attention to water quality if dealing with clay soils or with amendments such as gypsum; • strong focus on ensuring that the erosion processes considered are those of greatest importance to the field situation of concern; and • detailed description of both material and plot properties, to increase the potential for data to be applicable to a wider range of projects and investigations. Other important company procedures include: • For each project, the scientist or engineer responsible for analysing and reporting rainfall simulator data is present during the running of all field plots, as it is essential that they be aware of any specific conditions that may have developed when the plots were subjected to rain; and • Regular calibration of all equipment. In general, typical errors when rainfall simulation is carried out by inexperienced researchers include: • Failure to accurately measure rainfall rates (the most common error); • Inappropriate initial conditions, including wetting treatments; • Use of inappropriately small plots - relating to our concern at the erosion processes considered be those of genuine field relevance; • Inappropriate rainfall kinetic energies; and • Failure to observe critical processes operating on the study plots, such as saturation excess or the presence of impeding layers at shallow depths. Landloch regularly uses erodibility data to design stable batter profiles for minesite waste dumps. Subsequent monitoring of designed dumps has confirmed that modelled erosion rates are consistent with those subsequently measured under field conditions.

Hazard assessment for small torrent catchments - lessons learned

NASA Astrophysics Data System (ADS)

Eisl, Julia; Huebl, Johannes

2013-04-01

The documentation of extreme events as a part of the integral risk management cycle is an important basis for the analysis and assessment of natural hazards. In July 2011 a flood event occurred in the Wölzer-valley in the province of Styria, Austria. For this event at the "Wölzerbach" a detailed event documentation was carried out, gathering data about rainfall, runoff and sediment transport as well as information on damaged objects, infrastructure or crops using various sources. The flood was triggered by heavy rainfalls in two tributaries of the Wölzer-river. Though a rain as well as a discharge gaging station exists for the Wölzer-river, the torrents affected by the high intensity rainfalls are ungaged. For these ungaged torrent catchments the common methods for hazard assessment were evaluated. The back-calculation of the rainfall event was done using a new approach for precipitation analysis. In torrent catchments especially small-scale and high-intensity rainfall events are mainly responsible for extreme events. Austria's weather surveillance radar is operated by the air traffic service "AustroControl". The usually available dataset is interpreted and shows divergences especially when it comes to high intensity rainfalls. For this study the raw data of the radar were requested and analysed. Further on the event was back-calculated with different rainfall-runoff models, hydraulic models and sediment transport models to obtain calibration parameters for future use in hazard assessment for this region. Since there are often problems with woody debris different scenarios were simulated. The calibrated and plausible results from the runoff models were used for the comparison with empirical approaches used in the practical sector. For the planning of mitigation measures of the Schöttl-torrent, which is one of the affected tributaries of the Wölzer-river, a physical scale model was used in addition to the insights of the event analysis to design a check dam for sediment retention. As far as the transport capacity of the lower reaches is limited a balance had to be found between protection on the one hand and sediment connectivity to the Wölzer-river on the other. The lessons learned kicked off discussions for future hazard assessment especially concerning the use of rainfall data and design precipitation values for small torrent catchments. Also the comparison with empirical values showed the need for differentiated concepts for hazard analysis. Therefor recommendations for the use of spatial rainfall reduction factors as well as the demarcation of hazard maps using different event scenarios are proposed.

Simulation of rainfall-runoff for major flash flood events in Karachi

NASA Astrophysics Data System (ADS)

Zafar, Sumaira

2016-07-01

Metropolitan city Karachi has strategic importance for Pakistan. With the each passing decade the city is facing urban sprawl and rapid population growth. These rapid changes directly affecting the natural resources of city including its drainage pattern. Karachi has three major cities Malir River with the catchment area of 2252 sqkm and Lyari River has catchment area about 470.4 sqkm. These are non-perennial rivers and active only during storms. Change of natural surfaces into hard pavement causing an increase in rainfall-runoff response. Curve Number is increased which is now causing flash floods in the urban locality of Karachi. There is only one gauge installed on the upstream of the river but there no record for the discharge. Only one gauge located at the upstream is not sufficient for discharge measurements. To simulate the maximum discharge of Malir River rainfall (1985 to 2014) data were collected from Pakistan meteorological department. Major rainfall events use to simulate the rainfall runoff. Maximum rainfall-runoff response was recorded in during 1994, 2007 and 2013. This runoff causes damages and inundation in floodplain areas of Karachi. These flash flooding events not only damage the property but also cause losses of lives

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

PubMed Central

Harris, Amanda; Rahman, Sayma; Hossain, Faisal; Yarborough, Lance; Bagtzoglou, Amvrossios C.; Easson, Greg

2007-01-01

Increasingly available and a virtually uninterrupted supply of satellite-estimated rainfall data is gradually becoming a cost-effective source of input for flood prediction under a variety of circumstances. However, most real-time and quasi-global satellite rainfall products are currently available at spatial scales ranging from 0.25° to 0.50° and hence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scale flood events. This study assesses the question: what are the hydrologic implications of uncertainty of satellite rainfall data at the coarse scale? We investigated this question on the 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall product assessed was NASA's Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product called 3B41RT that is available in pseudo real time with a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data can improve application in flood prediction to some extent with the trade-off of more false alarms in peak flow. However, a more rational and regime-based adjustment procedure needs to be identified before the use of satellite data can be institutionalized among flood modelers. PMID:28903302

POLYNOMIAL-BASED DISAGGREGATION OF HOURLY RAINFALL FOR CONTINUOUS HYDROLOGIC SIMULATION

EPA Science Inventory

Hydrologic modeling of urban watersheds for designs and analyses of stormwater conveyance facilities can be performed in either an event-based or continuous fashion. Continuous simulation requires, among other things, the use of a time series of rainfall amounts. However, for urb...

On the relationship between the Indian summer monsoon rainfall and the EQUINOO in the CFSv2

NASA Astrophysics Data System (ADS)

Vishnu, S.; Francis, P. A.; Ramakrishna, S. S. V. S.; Shenoi, S. S. C.

2018-03-01

Several recent studies have shown that positive (negative) phase of Equatorial Indian Ocean Oscillation (EQUINOO) is favourable (unfavourable) to the Indian summer monsoon. However, many ocean-atmosphere global coupled models, including the state-of-the-art Climate Forecast System (CFS) version 2 have difficulty in reproducing this link realistically. In this study, we analyze the retrospective forecasts by the CFS model for the period 1982-2010 with an objective to identify the reasons behind the failure of the model to simulate the observed links between Indian summer monsoon and EQUINOO. It is found that, in the model hindcasts, the rainfall in the core monsoon region was mainly due to westward propagating synoptic scale systems, that originated from the vicinity of the tropical convergence zone (TCZ). Our analysis shows that unlike in observations, in the CFS, majority of positive (negative) EQUINOO events are associated with El Niño (La Niña) events in the Pacific. In addition to this, there is a strong link between EQUINOO and Indian Ocean Dipole (IOD) in the model. We show that, during the negative phase of EQUINOO/IOD, northward propagating TCZs remained stationary over the Bay of Bengal for longer period compared to the positive phase of EQUINOO/IOD. As a result, compared to the positive phase of EQUINOO/IOD, during a negative phase of EQUINOO/IOD, more westward propagating synoptic scale systems originated from the vicinity of TCZ and moved on to the core monsoon region, which resulted in higher rainfall over this region in the CFS. We further show that frequent, though short-lived, westward propagating systems, generated near the vicinity of TCZ over the Bay moved onto the mainland were responsible for less number of break monsoon spells during the negative phase of EQUINOO/IOD in the model hindcasts. This study underlines the necessity for improving the skill of the coupled models, particularly CFS model, to simulate the links between EQUINOO/IOD and the Indian summer monsoon for reliable predictions of seasonal and intraseasonal variation of Indian summer monsoon rainfall.

Sustainable management for rangelands in a variable climate: evidence and insights from northern Australia.

PubMed

O'Reagain, P J; Scanlan, J C

2013-03-01

Inter-annual rainfall variability is a major challenge to sustainable and productive grazing management on rangelands. In Australia, rainfall variability is particularly pronounced and failure to manage appropriately leads to major economic loss and environmental degradation. Recommended strategies to manage sustainably include stocking at long-term carrying capacity (LTCC) or varying stock numbers with forage availability. These strategies are conceptually simple but difficult to implement, given the scale and spatial heterogeneity of grazing properties and the uncertainty of the climate. This paper presents learnings and insights from northern Australia gained from research and modelling on managing for rainfall variability. A method to objectively estimate LTCC in large, heterogeneous paddocks is discussed, and guidelines and tools to tactically adjust stocking rates are presented. The possible use of seasonal climate forecasts (SCF) in management is also considered. Results from a 13-year grazing trial in Queensland show that constant stocking at LTCC was far more profitable and largely maintained land condition compared with heavy stocking (HSR). Variable stocking (VAR) with or without the use of SCF was marginally more profitable, but income variability was greater and land condition poorer than constant stocking at LTCC. Two commercial scale trials in the Northern Territory with breeder cows highlighted the practical difficulties of variable stocking and provided evidence that heavier pasture utilisation rates depress reproductive performance. Simulation modelling across a range of regions in northern Australia also showed a decline in resource condition and profitability under heavy stocking rates. Modelling further suggested that the relative value of variable v. constant stocking depends on stocking rate and land condition. Importantly, variable stocking may possibly allow slightly higher stocking rates without pasture degradation. Enterprise-level simulations run for breeder herds nevertheless show that poor economic performance can occur under constant stocking and even under variable stocking in some circumstances. Modelling and research results both suggest that a form of constrained flexible stocking should be applied to manage for climate variability. Active adaptive management and research will be required as future climate changes make managing for rainfall variability increasingly challenging.

Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

NASA Astrophysics Data System (ADS)

Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

2015-12-01

Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is the analysis of rainfall fields via first-order statistical properties, scaling functions, structure functions and spectral analysis, taking into account cloud-motion directions over mountainous slopes (windward/leeward side) and timing of the diurnal cycle. The analysis is developed for some Colombia's locations.

Parameter Tuning and Calibration of RegCM3 with MIT-Emanuel Cumulus Parameterization Scheme over CORDEX East Asian Domain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zou, Liwei; Qian, Yun; Zhou, Tianjun

2014-10-01

In this study, we calibrated the performance of regional climate model RegCM3 with Massachusetts Institute of Technology (MIT)-Emanuel cumulus parameterization scheme over CORDEX East Asia domain by tuning the selected seven parameters through multiple very fast simulated annealing (MVFSA) sampling method. The seven parameters were selected based on previous studies, which customized the RegCM3 with MIT-Emanuel scheme through three different ways by using the sensitivity experiments. The responses of model results to the seven parameters were investigated. Since the monthly total rainfall is constrained, the simulated spatial pattern of rainfall and the probability density function (PDF) distribution of daily rainfallmore » rates are significantly improved in the optimal simulation. Sensitivity analysis suggest that the parameter “relative humidity criteria” (RH), which has not been considered in the default simulation, has the largest effect on the model results. The responses of total rainfall over different regions to RH were examined. Positive responses of total rainfall to RH are found over northern equatorial western Pacific, which are contributed by the positive responses of explicit rainfall. Followed by an increase of RH, the increases of the low-level convergence and the associated increases in cloud water favor the increase of the explicit rainfall. The identified optimal parameters constrained by the total rainfall have positive effects on the low-level circulation and the surface air temperature. Furthermore, the optimized parameters based on the extreme case are suitable for a normal case and the model’s new version with mixed convection scheme.« less

Revisiting the latent heat nudging scheme for the rainfall assimilation of a simulated convective storm

NASA Astrophysics Data System (ADS)

Leuenberger, D.; Rossa, A.

2007-12-01

Next-generation, operational, high-resolution numerical weather prediction models require economical assimilation schemes for radar data. In the present study we evaluate and characterise the latent heat nudging (LHN) rainfall assimilation scheme within a meso-γ scale NWP model in the framework of identical twin simulations of an idealised supercell storm. Consideration is given to the model’s dynamical response to the forcing as well as to the sensitivity of the LHN scheme to uncertainty in the observations and the environment. The results indicate that the LHN scheme is well able to capture the dynamical structure and the right rainfall amount of the storm in a perfect environment. This holds true even in degraded environments but a number of important issues arise. In particular, changes in the low-level humidity field are found to affect mainly the precipitation amplitude during the assimilation with a fast adaptation of the storm to the system dynamics determined by the environment during the free forecast. A constant bias in the environmental wind field, on the other hand, has the potential to render a successful assimilation with the LHN scheme difficult, as the velocity of the forcing is not consistent with the system propagation speed determined by the wind. If the rainfall forcing moves too fast, the system propagation is supported and the assimilated storm and forecasts initialised therefrom develop properly. A too slow forcing, on the other hand, can decelerate the system and eventually disturb the system dynamics by decoupling the low-level moisture inflow from the main updrafts during the assimilation. This distortion is sustained in the free forecast. It has further been found that a sufficient temporal resolution of the rainfall input is crucial for the successful assimilation of a fast moving, coherent convective storm and that the LHN scheme, when applied to a convective storm, appears to necessitate a careful tuning.

Application of a process-based shallow landslide hazard model over a broad area in Central Italy

USGS Publications Warehouse

Gioia, Eleonora; Speranza, Gabriella; Ferretti, Maurizio; Godt, Jonathan W.; Baum, Rex L.; Marincioni, Fausto

2015-01-01

Process-based models are widely used for rainfall-induced shallow landslide forecasting. Previous studies have successfully applied the U.S. Geological Survey’s Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (Baum et al. 2002) to compute infiltration-driven changes in the hillslopes’ factor of safety on small scales (i.e., tens of square kilometers). Soil data input for such models are difficult to obtain across larger regions. This work describes a novel methodology for the application of TRIGRS over broad areas with relatively uniform hydrogeological properties. The study area is a 550-km2 region in Central Italy covered by post-orogenic Quaternary sediments. Due to the lack of field data, we assigned mechanical and hydrological property values through a statistical analysis based on literature review of soils matching the local lithologies. We calibrated the model using rainfall data from 25 historical rainfall events that triggered landslides. We compared the variation of pressure head and factor of safety with the landslide occurrence to identify the best fitting input conditions. Using calibrated inputs and a soil depth model, we ran TRIGRS for the study area. Receiver operating characteristic (ROC) analysis, comparing the model’s output with a shallow landslide inventory, shows that TRIGRS effectively simulated the instability conditions in the post-orogenic complex during historical rainfall scenarios. The implication of this work is that rainfall-induced landslides over large regions may be predicted by a deterministic model, even where data on geotechnical and hydraulic properties as well as temporal changes in topography or subsurface conditions are not available.

The western Pacific monsoon in CMIP5 models: Model evaluation and projections

NASA Astrophysics Data System (ADS)

Brown, Josephine R.; Colman, Robert A.; Moise, Aurel F.; Smith, Ian N.

2013-11-01

ability of 35 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to simulate the western Pacific (WP) monsoon is evaluated over four representative regions around Timor, New Guinea, the Solomon Islands and Palau. Coupled model simulations are compared with atmosphere-only model simulations (with observed sea surface temperatures, SSTs) to determine the impact of SST biases on model performance. Overall, the CMIP5 models simulate the WP monsoon better than previous-generation Coupled Model Intercomparison Project Phase 3 (CMIP3) models, but some systematic biases remain. The atmosphere-only models are better able to simulate the seasonal cycle of zonal winds than the coupled models, but display comparable biases in the rainfall. The CMIP5 models are able to capture features of interannual variability in response to the El Niño-Southern Oscillation. In climate projections under the RCP8.5 scenario, monsoon rainfall is increased over most of the WP monsoon domain, while wind changes are small. Widespread rainfall increases at low latitudes in the summer hemisphere appear robust as a large majority of models agree on the sign of the change. There is less agreement on rainfall changes in winter. Interannual variability of monsoon wet season rainfall is increased in a warmer climate, particularly over Palau, Timor and the Solomon Islands. A subset of the models showing greatest skill in the current climate confirms the overall projections, although showing markedly smaller rainfall increases in the western equatorial Pacific. The changes found here may have large impacts on Pacific island countries influenced by the WP monsoon.

Combined effects of constant versus variable intensity simulated rainfall and reduced tillage management on cotton preemergence herbicide runoff.

PubMed

Potter, Thomas L; Truman, Clint C; Strickland, Timothy C; Bosch, David D; Webster, Theodore M; Franklin, Dorcas H; Bednarz, Craig W

2006-01-01

Pesticide runoff research relies heavily on rainfall simulation experiments. Most are conducted at a constant intensity, i.e., at a fixed rainfall rate; however, large differences in natural rainfall intensity is common. To assess implications we quantified runoff of two herbicides, fluometuron and pendimethalin, and applied preemergence after planting cotton on Tifton loamy sand. Rainfall at constant and variable intensity patterns representative of late spring thunderstorms in the Atlantic Coastal Plain region of Georgia (USA) were simulated on 6-m2 plots under strip- (ST) and conventional-tillage (CT) management. The variable pattern produced significantly higher runoff rates of both compounds from CT but not ST plots. However, on an event-basis, runoff totals (% applied) were not significantly different, with one exception: fluometuron runoff from CT plots. There was about 25% more fluometuron runoff with the variable versus the constant intensity pattern (P = 0.10). Study results suggest that conduct of simulations using variable intensity storm patterns may provide more representative rainfall simulation-based estimates of pesticide runoff and that the greatest impacts will be observed with CT. The study also found significantly more fluometuron in runoff from ST than CT plots. Further work is needed to determine whether this behavior may be generalized to other active ingredients with similar properties [low K(oc) (organic carbon partition coefficient) approximately 100 mL g(-1); high water solubility approximately 100 mg L(-1)]. If so, it should be considered when making tillage-specific herbicide recommendations to reduce runoff potential.

TRMM Latent Heating Retrieval and Comparisons with Field Campaigns and Large-Scale Analyses

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Takayabu, Yukuri; Lang, S.; Shige, S.; Olson, W.; Hou, A.; Jiang, X.; Zhang, C.; Lau, W.; Krishnamurti, T.;

Mapping the Impact of Aerosol-Cloud Interactions on Cloud Formation and Warm-season Rainfall in Mountainous Regions Using Observations and Models

NASA Astrophysics Data System (ADS)

Duan, Yajuan

Light rainfall (< 3 mm/hr) amounts to 30-70% of the annual water budget in the Southern Appalachian Mountains (SAM), a mid-latitude mid-mountain system in the SE CONUS. Topographic complexity favors the diurnal development of regional-scale convergence patterns that provide the moisture source for low-level clouds and fog (LLCF). Low-level moisture and cloud condensation nuclei (CCN) are distributed by ridge-valley circulations favoring LLCF formation that modulate the diurnal cycle of rainfall especially the mid-day peak. The overarching objective of this dissertation is to advance the quantitative understanding of the indirect effect of aerosols on the diurnal cycle of LLCF and warm-season precipitation in mountainous regions generally, and in the SAM in particular, for the purpose of improving the representation of orographic precipitation processes in remote sensing retrievals and physically-based models. The research approach consists of integrating analysis of in situ observations from long-term observation networks and an intensive field campaign, multi-sensor satellite data, and modeling studies. In the first part of this dissertation, long-term satellite observations are analyzed to characterize the spatial and temporal variability of LLCF and to elucidate the physical basis of the space-time error structure in precipitation retrievals. Significantly underestimated precipitation errors are attributed to variations in low-level rainfall microstructure undetected by satellites. Column model simulations including observed LLCF microphysics demonstrate that seeder-feeder interactions (SFI) among upper-level precipitation and LLCF contribute to an three-fold increase in observed rainfall accumulation and can enhance surface rainfall by up to ten-fold. The second part of this dissertation examines the indirect effect of aerosols on cloud formation and warm-season daytime precipitation in the SAM. A new entraining spectral cloud parcel model was developed and applied to provide the first assessment of aerosol-cloud interactions in the early development of mid-day cumulus congestus over the inner SAM. Leveraging comprehensive measurements from the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014, model results indicate that simulated spectra with a low value of condensation coefficient (0.01) are in good agreement with IPHEx aircraft observations. Further, to explore sensitivity of warm-season precipitation processes to CCN characteristics, detailed intercomparisons of Weather Research and Forecasting (WRF) model simulations using IPHEx and standard continental CCN spectra were conducted. The simulated CDNC using the local spectrum show better agreement with IPHEx airborne observations and better replicate the widespread low-level cloudiness around mid-day over the inner region. The local spectrum simulation also indicate suppressed early precipitation, enhanced ice processes tied to more vigorous vertical development of individual storm cells. The studied processes here are representative of dominant moist atmospheric processes in complex terrain and cloud forests in the humid tropics and extra-tropics, thus findings from this research in the SAM are transferable to mountainous areas elsewhere.

The Microphysical Structure of Extreme Precipitation as Inferred from Ground-Based Raindrop Spectra.

NASA Astrophysics Data System (ADS)

Uijlenhoet, Remko; Smith, James A.; Steiner, Matthias

2003-05-01

The controls on the variability of raindrop size distributions in extreme rainfall and the associated radar reflectivity-rain rate relationships are studied using a scaling-law formalism for the description of raindrop size distributions and their properties. This scaling-law formalism enables a separation of the effects of changes in the scale of the raindrop size distribution from those in its shape. Parameters controlling the scale and shape of the scaled raindrop size distribution may be related to the microphysical processes generating extreme rainfall. A global scaling analysis of raindrop size distributions corresponding to rain rates exceeding 100 mm h1, collected during the 1950s with the Illinois State Water Survey raindrop camera in Miami, Florida, reveals that extreme rain rates tend to be associated with conditions in which the variability of the raindrop size distribution is strongly number controlled (i.e., characteristic drop sizes are roughly constant). This means that changes in properties of raindrop size distributions in extreme rainfall are largely produced by varying raindrop concentrations. As a result, rainfall integral variables (such as radar reflectivity and rain rate) are roughly proportional to each other, which is consistent with the concept of the so-called equilibrium raindrop size distribution and has profound implications for radar measurement of extreme rainfall. A time series analysis for two contrasting extreme rainfall events supports the hypothesis that the variability of raindrop size distributions for extreme rain rates is strongly number controlled. However, this analysis also reveals that the actual shapes of the (measured and scaled) spectra may differ significantly from storm to storm. This implies that the exponents of power-law radar reflectivity-rain rate relationships may be similar, and close to unity, for different extreme rainfall events, but their prefactors may differ substantially. Consequently, there is no unique radar reflectivity-rain rate relationship for extreme rain rates, but the variability is essentially reduced to one free parameter (i.e., the prefactor). It is suggested that this free parameter may be estimated on the basis of differential reflectivity measurements in extreme rainfall.

Observed and simulated hydrologic response for a first-order catchment during extreme rainfall 3 years after wildfire disturbance

USGS Publications Warehouse

Ebel, Brian A.; Rengers, Francis K.; Tucker, Gregory E.

2016-01-01

Hydrologic response to extreme rainfall in disturbed landscapes is poorly understood because of the paucity of measurements. A unique opportunity presented itself when extreme rainfall in September 2013 fell on a headwater catchment (i.e., <1 ha) in Colorado, USA that had previously been burned by a wildfire in 2010. We compared measurements of soil-hydraulic properties, soil saturation from subsurface sensors, and estimated peak runoff during the extreme rainfall with numerical simulations of runoff generation and subsurface hydrologic response during this event. The simulations were used to explore differences in runoff generation between the wildfire-affected headwater catchment, a simulated unburned case, and for uniform versus spatially variable parameterizations of soil-hydraulic properties that affect infiltration and runoff generation in burned landscapes. Despite 3 years of elapsed time since the 2010 wildfire, observations and simulations pointed to substantial surface runoff generation in the wildfire-affected headwater catchment by the infiltration-excess mechanism while no surface runoff was generated in the unburned case. The surface runoff generation was the result of incomplete recovery of soil-hydraulic properties in the burned area, suggesting recovery takes longer than 3 years. Moreover, spatially variable soil-hydraulic property parameterizations produced longer duration but lower peak-flow infiltration-excess runoff, compared to uniform parameterization, which may have important hillslope sediment export and geomorphologic implications during long duration, extreme rainfall. The majority of the simulated surface runoff in the spatially variable cases came from connected near-channel contributing areas, which was a substantially smaller contributing area than the uniform simulations.

Causes of Long-Term Drought in the United States Great Plains

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Suarez, Max J.; Pegion, Philip J.; Koster, Randal

2002-01-01

The United States Great Plains (USGP) experienced a number of multi-year droughts during the last century, most notably the droughts of the 1930s and 1950s. This study examines the causes of such droughts using ensembles of long term (1930-1999) simulations carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTs). The results show that the model produces long-term (multi-year) variations in the USGP precipitation that are similar to those observed. A correlative analysis suggests that the ensemble mean low frequency (time scales longer than about 6 years) rainfall variations in the USGP are linked to a pan-Pacific pattern of SST variability that is the leading empirical orthogonal function (EOF) in the low frequency SST data. The link between the SST and the Great Plains precipitation is confirmed in idealized AGCM simulations, in which the model is forced by the 2 polarities of the pan-Pacific SST pattern. The idealized simulations further show that it is primarily the tropical part of the SST anomalies that influence the USGP. As such, the USGP tend to have above normal precipitation when the tropical Pacific SSTs are above normal, while there is a tendency for drought when the tropical SSTs are cold. The upper tropospheric response to the pan-Pacific SST EOF shows a global-scale pattern with a strong wave response in the Pacific and a substantial zonally-symmetric component in which USGP pluvial (drought) conditions are associated with reduced (enhanced) heights throughout the extra-tropics. The potential predictability of rainfall in the USGP associated with SSTs is rather modest, with on average about 1/3 of the total low frequency rainfall variance forced by SST anomalies. Further idealized experiments with climatological SST, suggest that the remaining low frequency variance in the USGP precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a six-fold increase in the variance in annual USGP precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce year-to-year memory in the hydrological cycle that is consistent with a red noise process, in which the low frequencies in the deep soil are the result of integrating a net forcing (precipitation-evaporation-runoff) that is white noise on interannual time scales. As such, the role of low frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.

The October 2015 flash-floods in south eastern France: hydrological analyses, inundation mapping and impact estimations

NASA Astrophysics Data System (ADS)

Payrastre, Olivier; Bourgin, François; Lebouc, Laurent; Le Bihan, Guillaume; Gaume, Eric

2017-04-01

The October 2015 flash-floods in south eastern France caused more than twenty fatalities, high damages and large economic losses in high density urban areas of the Mediterranean coast, including the cities of Mandelieu-La Napoule, Cannes and Antibes. Following a post event survey and preliminary analyses conducted within the framework of the Hymex project, we set up an entire simulation chain at the regional scale to better understand this outstanding event. Rainfall-runoff simulations, inundation mapping and a first estimation of the impacts are conducted following the approach developed and successfully applied for two large flash-flood events in two different French regions (Gard in 2002 and Var in 2010) by Le Bihan (2016). A distributed rainfall-runoff model applied at high resolution for the whole area - including numerous small ungauged basins - is used to feed a semi-automatic hydraulic approach (Cartino method) applied along the river network - including small tributaries. Estimation of the impacts is then performed based on the delineation of the flooded areas and geographic databases identifying buildings and population at risk.

Impact of rainfall pattern on interrill erosion process

USDA-ARS?s Scientific Manuscript database

The impact of rainfall pattern on the interrill erosion process is not fully understood despite its importance. Systematic rainfall simulation experiments involving different rain intensities, stages, intensity sequences, and surface cover conditions were conducted to investigate the impacts of rain...

Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2017-04-01

Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model performance. Results were analyzed at three ranges of scales identified in the fractal analysis and confirmed in the modeling work. The sensitivity of the model to small-scale rainfall variability was discussed as well.

Synchrony, compensatory dynamics, and the functional trait basis of phenological diversity in a tropical dry forest tree community: effects of rainfall seasonality

NASA Astrophysics Data System (ADS)

Lasky, Jesse R.; Uriarte, María; Muscarella, Robert

2016-11-01

Interspecific variation in phenology is a key axis of functional diversity, potentially mediating how communities respond to climate change. The diverse drivers of phenology act across multiple temporal scales. For example, abiotic constraints favor synchronous reproduction (positive covariance among species), while biotic interactions can favor synchrony or compensatory dynamics (negative covariance). We used wavelet analyses to examine phenology of community flower and seed production for 45 tree species across multiple temporal scales in a tropical dry forest in Puerto Rico with marked rainfall seasonality. We asked three questions: (1) do species exhibit synchronous or compensatory temporal dynamics in reproduction, (2) do interspecific differences in phenology reflect variable responses to rainfall, and (3) is interspecific variation in phenology and response to a major drought associated with functional traits that mediate responses to moisture? Community-level flowering was synchronized at seasonal scales (˜5-6 mo) and at short scales (˜1 mo, following rainfall). However, seed rain exhibited significant compensatory dynamics at intraseasonal scales (˜3 mo), suggesting interspecific variation in temporal niches. Species with large leaves (associated with sensitivity to water deficit) peaked in reproduction synchronously with the peak of seasonal rainfall (˜5 mo scale). By contrast, species with high wood specific gravity (associated with drought resistance) tended to flower in drier periods. Flowering of tall species and those with large leaves was most tightly linked to intraseasonal (˜2 mo scale) rainfall fluctuations. Although the 2015 drought dramatically reduced community-wide reproduction, functional traits were not associated with the magnitude of species-specific declines. Our results suggest opposing drivers of synchronous versus compensatory dynamics at different temporal scales. Phenology associations with functional traits indicated that distinct strategies for coping with seasonality underlie phenological diversity. Observed drought responses highlight the importance of non-linear community responses to climate. Community phenology exhibits scale-specific patterns highlighting the need for multi-scale approaches to community dynamics.

The added value of convection permitting simulations of extreme precipitation events over the eastern Mediterranean

NASA Astrophysics Data System (ADS)

Zittis, G.; Bruggeman, A.; Camera, C.; Hadjinicolaou, P.; Lelieveld, J.

2017-07-01

Climate change is expected to substantially influence precipitation amounts and distribution. To improve simulations of extreme rainfall events, we analyzed the performance of different convection and microphysics parameterizations of the WRF (Weather Research and Forecasting) model at very high horizontal resolutions (12, 4 and 1 km). Our study focused on the eastern Mediterranean climate change hot-spot. Five extreme rainfall events over Cyprus were identified from observations and were dynamically downscaled from the ERA-Interim (EI) dataset with WRF. We applied an objective ranking scheme, using a 1-km gridded observational dataset over Cyprus and six different performance metrics, to investigate the skill of the WRF configurations. We evaluated the rainfall timing and amounts for the different resolutions, and discussed the observational uncertainty over the particular extreme events by comparing three gridded precipitation datasets (E-OBS, APHRODITE and CHIRPS). Simulations with WRF capture rainfall over the eastern Mediterranean reasonably well for three of the five selected extreme events. For these three cases, the WRF simulations improved the ERA-Interim data, which strongly underestimate the rainfall extremes over Cyprus. The best model performance is obtained for the January 1989 event, simulated with an average bias of 4% and a modified Nash-Sutcliff of 0.72 for the 5-member ensemble of the 1-km simulations. We found overall added value for the convection-permitting simulations, especially over regions of high-elevation. Interestingly, for some cases the intermediate 4-km nest was found to outperform the 1-km simulations for low-elevation coastal parts of Cyprus. Finally, we identified significant and inconsistent discrepancies between the three, state of the art, gridded precipitation datasets for the tested events, highlighting the observational uncertainty in the region.

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

PubMed

van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

2015-05-01

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

2015-07-01

This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

Mechanisms for Diurnal Variability of Global Tropical Rainfall Observed from TRMM

NASA Technical Reports Server (NTRS)

Yang, Song; Smith, Eric A.

2004-01-01

The behavior and various controls of diurnal variability in tropical-subtropical rainfall are investigated using Tropical Rainfall Measuring Mission (TRMM) precipitation measurements retrieved from: (1) TRMM Microwave Imager (TMI), (2) Precipitation Radar (PR), and (3) TMI/PR Combined, standard level 2 algorithms for the 1998 annual cycle. Results show that the diurnal variability characteristics of precipitation are consistent for all three algorithms, providing assurance that TRMM retrievals are providing consistent estimates of rainfall variability. As anticipated, most ocean areas exhibit more rainfall at night, while over most land areas rainfall peaks during daytime ,however, various important exceptions are found. The dominant feature of the oceanic diurnal cycle is a rainfall maximum in late-evening/early-morning (LE-EM) hours, while over land the dominant maximum occurs in the mid- to late-afternoon (MLA). In conjunction with these maxima are pronounced seasonal variations of the diurnal amplitudes. Amplitude analysis shows that the diurnal pattern and its seasonal evolution are closely related to the rainfall accumulation pattern and its seasonal evolution. In addition, the horizontal distribution of diurnal variability indicates that for oceanic rainfall there is a secondary MLA maximum, co-existing with the LE-EM maximum, at latitudes dominated by large scale convergence and deep convection. Analogously, there is a preponderance for an LE-EM maximum over land, co-existing with the stronger MLA maximum, although it is not evident that this secondary continental feature is closely associated with the large scale circulation. The ocean results clearly indicate that rainfall diurnal variability associated with large scale convection is an integral part of the atmospheric general circulation.

Rainfall threshold definition using an entropy decision approach and radar data

NASA Astrophysics Data System (ADS)

Montesarchio, V.; Ridolfi, E.; Russo, F.; Napolitano, F.

2011-07-01

Flash flood events are floods characterised by a very rapid response of basins to storms, often resulting in loss of life and property damage. Due to the specific space-time scale of this type of flood, the lead time available for triggering civil protection measures is typically short. Rainfall threshold values specify the amount of precipitation for a given duration that generates a critical discharge in a given river cross section. If the threshold values are exceeded, it can produce a critical situation in river sites exposed to alluvial risk. It is therefore possible to directly compare the observed or forecasted precipitation with critical reference values, without running online real-time forecasting systems. The focus of this study is the Mignone River basin, located in Central Italy. The critical rainfall threshold values are evaluated by minimising a utility function based on the informative entropy concept and by using a simulation approach based on radar data. The study concludes with a system performance analysis, in terms of correctly issued warnings, false alarms and missed alarms.

Climatic trends over Ethiopia: regional signals and drivers

USGS Publications Warehouse

Jury, Mark R.; Funk, Christopher C.

2013-01-01

This study analyses observed and projected climatic trends over Ethiopia, through analysis of temperature and rainfall records and related meteorological fields. The observed datasets include gridded station records and reanalysis products; while projected trends are analysed from coupled model simulations drawn from the IPCC 4th Assessment. Upward trends in air temperature of + 0.03 °C year−1 and downward trends in rainfall of − 0.4 mm month−1 year−1 have been observed over Ethiopia's southwestern region in the period 1948-2006. These trends are projected to continue to 2050 according to the Geophysical Fluid Dynamics Lab model using the A1B scenario. Large scale forcing derives from the West Indian Ocean where significant warming and increased rainfall are found. Anticyclonic circulations have strengthened over northern and southern Africa, limiting moisture transport from the Gulf of Guinea and Congo. Changes in the regional Walker and Hadley circulations modulate the observed and projected climatic trends. Comparing past and future patterns, the key features spread westward from Ethiopia across the Sahel and serve as an early warning of potential impacts.

Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

NASA Astrophysics Data System (ADS)

Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

2012-08-01

This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

NASA Astrophysics Data System (ADS)

Staley, Dennis; Negri, Jacquelyn; Kean, Jason

2016-04-01

Population expansion into fire-prone steeplands has resulted in an increase in post-fire debris-flow risk in the western United States. Logistic regression methods for determining debris-flow likelihood and the calculation of empirical rainfall intensity-duration thresholds for debris-flow initiation represent two common approaches for characterizing hazard and reducing risk. Logistic regression models are currently being used to rapidly assess debris-flow hazard in response to design storms of known intensities (e.g. a 10-year recurrence interval rainstorm). Empirical rainfall intensity-duration thresholds comprise a major component of the United States Geological Survey (USGS) and the National Weather Service (NWS) debris-flow early warning system at a regional scale in southern California. However, these two modeling approaches remain independent, with each approach having limitations that do not allow for synergistic local-scale (e.g. drainage-basin scale) characterization of debris-flow hazard during intense rainfall. The current logistic regression equations consider rainfall a unique independent variable, which prevents the direct calculation of the relation between rainfall intensity and debris-flow likelihood. Regional (e.g. mountain range or physiographic province scale) rainfall intensity-duration thresholds fail to provide insight into the basin-scale variability of post-fire debris-flow hazard and require an extensive database of historical debris-flow occurrence and rainfall characteristics. Here, we present a new approach that combines traditional logistic regression and intensity-duration threshold methodologies. This method allows for local characterization of both the likelihood that a debris-flow will occur at a given rainfall intensity, the direct calculation of the rainfall rates that will result in a given likelihood, and the ability to calculate spatially explicit rainfall intensity-duration thresholds for debris-flow generation in recently burned areas. Our approach synthesizes the two methods by incorporating measured rainfall intensity into each model variable (based on measures of topographic steepness, burn severity and surface properties) within the logistic regression equation. This approach provides a more realistic representation of the relation between rainfall intensity and debris-flow likelihood, as likelihood values asymptotically approach zero when rainfall intensity approaches 0 mm/h, and increase with more intense rainfall. Model performance was evaluated by comparing predictions to several existing regional thresholds. The model, based upon training data collected in southern California, USA, has proven to accurately predict rainfall intensity-duration thresholds for other areas in the western United States not included in the original training dataset. In addition, the improved logistic regression model shows promise for emergency planning purposes and real-time, site-specific early warning. With further validation, this model may permit the prediction of spatially-explicit intensity-duration thresholds for debris-flow generation in areas where empirically derived regional thresholds do not exist. This improvement would permit the expansion of the early-warning system into other regions susceptible to post-fire debris flow.

SUBPIXEL-SCALE RAINFALL VARIABILITY AND THE EFFECTS ON SEPARATION OF RADAR AND GAUGE RAINFALL ERRORS

EPA Science Inventory

One of the primary sources of the discrepancies between radar-based rainfall estimates and rain gauge measurements is the point-area difference, i.e., the intrinsic difference in the spatial dimensions of the rainfall fields that the respective data sets are meant to represent. ...

Historical simulations and climate change projections over India by NCAR CCSM4: CMIP5 vs. NEX-GDDP

NASA Astrophysics Data System (ADS)

Sahany, Sandeep; Mishra, Saroj Kanta; Salunke, Popat

2018-03-01

A new bias-corrected statistically downscaled product, namely, the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), has recently been developed by NASA to help the scientific community in climate change impact studies at local to regional scale. In this work, the product is validated over India and its added value as compared to its CMIP5 counterpart for the NCAR CCSM4 model is analyzed, followed by climate change projections under the RCP8.5 global warming scenario using the two datasets for the variables daily maximum 2-m air temperature (Tmax), daily minimum 2-m air temperature (Tmin), and rainfall. It is found that, overall, the CCSM4-NEX-GDDP significantly reduces many of the biases in CCSM4-CMIP5 for the historical simulations; however, some biases such as the significant overestimation in the frequency of occurrence in the lower tail of the Tmax and Tmin still remain. In regard to rainfall, an important value addition in CCSM4-NEX-GDDP is the alleviation of the significant underestimation of rainfall extremes found in CCSM4-CMIP5. The projected Tmax from CCSM4-NEX-GDDP are in general higher than that projected by CCSM4-CMIP5, suggesting that the risks of heat waves and very hot days could be higher than that projected by the latter. CCSM4-NEX-GDDP projects the frequency of occurrence of the upper extreme values of historical Tmax to increase by a factor of 100 towards the end of century (as opposed to a factor of 10 increase projected by CCSM4-CMIP5). In regard to rainfall, both CCSM4-CMIP5 and CCSM4-NEX-GDDP project an increase in annual rainfall over India under the RCP8.5 global warming scenario progressively from the near term through the far term. However, CCSM4-NEX-GDDP consistently projects a higher magnitude of increase and over a larger area as compared to that projected by CCSM4-CMIP5. Projected daily rainfall distributions from CCSM4-CMIP5 and CCSM4-NEX-GDDP suggest the occurrence of events that have no historical precedents. Worth noting is that the extreme daily rainfall values projected by CCSM4-NEX-GDDP are two to three times larger than that projected by CCSM4-CMIP5.

Impact of Synoptic-Scale Factors on Rainfall Forecast in Different Stages of a Persistent Heavy Rainfall Event in South China

NASA Astrophysics Data System (ADS)

Zhang, Murong; Meng, Zhiyong

2018-04-01

This study investigates the stage-dependent rainfall forecast skills and the associated synoptic-scale features in a persistent heavy rainfall event in south China, Guangdong Province, during 29-31 March 2014, using operational global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts. This persistent rainfall was divided into two stages with a better precipitation forecast skill in Stage 2 (S2) than Stage 1 (S1) although S2 had a longer lead time. Using ensemble-based sensitivity analysis, key synoptic-scale factors that affected the rainfall were diagnosed by correlating the accumulated precipitation of each stage to atmospheric state variables in the middle of respective stage. The precipitation in both stages was found to be significantly correlated with midlevel trough, low-level vortex, and particularly the low-level jet on the southeast flank of the vortex and its associated moisture transport. The rainfall forecast skill was mainly determined by the forecast accuracy in the location of the low-level jet, which was possibly related to the different juxtapositions between the direction of the movement of the low-level vortex and the orientation of the low-level jet. The uncertainty in rainfall forecast in S1 was mainly from the location uncertainty of the low-level jet, while the uncertainty in rainfall forecast in S2 was mainly from the width uncertainty of the low-level jet with the relatively accurate location of the low-level jet.

The Effects of More Extreme Rainfall Patterns on Infiltration and Nutrient Losses in Agricultural Soils

NASA Astrophysics Data System (ADS)

Hess, L.; Basso, B.; Hinckley, E. L. S.; Robertson, G. P.; Matson, P. A.

2015-12-01

In the coming century, the proportion of total rainfall that falls in heavy storm events is expected to increase in many areas, especially in the US Midwest, a major agricultural region. These changes in rainfall patterns may have consequences for hydrologic flow and nutrient losses, especially in agricultural soils, with potentially negative consequences for receiving ground- and surface waters. We used a tracer experiment to examine how more extreme rainfall patterns may affect the movement of water and solutes through an agricultural soil profile in the upper Midwest, and to what extent tillage may moderate these effects. Two rainfall patterns were created with 5m x 5m rainout shelters at the Kellogg Biological Station LTER site in replicated plots with either conventional tillage or no-till management. Control rainfall treatments received water 3x per week, and extreme rainfall treatments received the same total amount of water but once every two weeks, to simulate less frequent but larger storms. In April 2015, potassium bromide (KBr) was added as a conservative tracer of water flow to all plots, and Br- concentrations in soil water at 1.2m depth were measured weekly from April through July. Soil water Br- concentrations increased and peaked more quickly under the extreme rainfall treatment, suggesting increased infiltration and solute transfer to depth compared to soils exposed to control rainfall patterns. Soil water Br- also increased and peaked more quickly in no-till than in conventional tillage treatments, indicating differences in flow paths between management systems. Soil moisture measured every 15 minutes at 10, 40, and 100cm depths corroborates tracer experiment results: rainfall events simulated in extreme rainfall treatments led to large increases in deep soil moisture, while the smaller rainfall events simulated under control conditions did not. Deep soil moisture in no-till treatments also increased sooner after water application as compared to in conventional soils. Our results suggest that exposure to more extreme rainfall patterns will likely increase infiltration depth and nutrient losses in agricultural soils. In particular, soils under no-till management, which leads to development of preferential flow paths, may be particularly vulnerable to vertical nutrient losses.

Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Lin, Xin; Zhang, Sara Q.; Hou, Arthur Y.

2006-01-01

Global microwave rainfall retrievals from a 5-satellite constellation, including TMI from TRMM, SSWI from DMSP F13, F14 and F15, and AMSR-E from EOS-AQUA, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) using a 1-D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses and forecasts is examined at various temporal and spatial scales. This study demonstrates that the 1-D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over the land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly-mean and 6-hour time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1-D VCA algorithm, by compensating for errors in the model s moist time-tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall-assimilation m especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicates that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity are more realistically captured across the front. Short-term forecasts using initial conditions assimilated with rainfall data also show slight improvements. 1

Design of a reliable and operational landslide early warning system at regional scale

NASA Astrophysics Data System (ADS)

Calvello, Michele; Piciullo, Luca; Gariano, Stefano Luigi; Melillo, Massimo; Brunetti, Maria Teresa; Peruccacci, Silvia; Guzzetti, Fausto

2017-04-01

Landslide early warning systems at regional scale are used to warn authorities, civil protection personnel and the population about the occurrence of rainfall-induced landslides over wide areas, typically through the prediction and measurement of meteorological variables. A warning model for these systems must include a regional correlation law and a decision algorithm. A regional correlation law can be defined as a functional relationship between rainfall and landslides; it is typically based on thresholds of rainfall indicators (e.g., cumulated rainfall, rainfall duration) related to different exceedance probabilities of landslide occurrence. A decision algorithm can be defined as a set of assumptions and procedures linking rainfall thresholds to warning levels. The design and the employment of an operational and reliable early warning system for rainfall-induced landslides at regional scale depend on the identification of a reliable correlation law as well as on the definition of a suitable decision algorithm. Herein, a five-step process chain addressing both issues and based on rainfall thresholds is proposed; the procedure is tested in a landslide-prone area of the Campania region in southern Italy. To this purpose, a database of 96 shallow landslides triggered by rainfall in the period 2003-2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall thresholds are defined applying a frequentist method to reconstructed rainfall conditions triggering landslides in the test area. In the second step, several thresholds at different exceedance probabilities are evaluated, and different percentile combinations are selected for the activation of three warning levels. Subsequently, within steps three and four, the issuing of warning levels is based on the comparison, over time and for each combination, between the measured rainfall and the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system is selected evaluating the model performance in terms of success and error indicators by means of the "event, duration matrix, performance" (EDuMaP) method.

Rainfall-runoff characteristics and effects of increased urban density on streamflow and infiltration in the eastern part of the San Jacinto River basin, Riverside County, California

USGS Publications Warehouse

Guay, Joel R.

2002-01-01

To better understand the rainfall-runoff characteristics of the eastern part of the San Jacinto River Basin and to estimate the effects of increased urbanization on streamflow, channel infiltration, and land-surface infiltration, a long-term (1950?98) time series of monthly flows in and out of the channels and land surfaces were simulated using the Hydrologic Simulation Program- FORTRAN (HSPF) rainfall-runoff model. Channel and land-surface infiltration includes rainfall or runoff that infiltrates past the zone of evapotranspiration and may become ground-water recharge. The study area encompasses about 256 square miles of the San Jacinto River drainage basin in Riverside County, California. Daily streamflow (for periods with available data between 1950 and 1998), and daily rainfall and evaporation (1950?98) data; monthly reservoir storage data (1961?98); and estimated mean annual reservoir inflow data (for 1974 conditions) were used to calibrate the rainfall-runoff model. Measured and simulated mean annual streamflows for the San Jacinto River near San Jacinto streamflow-gaging station (North-South Fork subbasin) for 1950?91 and 1997?98 were 14,000 and 14,200 acre-feet, respectively, a difference of 1.4 percent. The standard error of the mean for measured and simulated annual streamflow in the North-South Fork subbasin was 3,520 and 3,160 acre-feet, respectively. Measured and simulated mean annual streamflows for the Bautista Creek streamflow-gaging station (Bautista Creek subbasin) for 1950?98 were 980 acre-feet and 991 acre-feet, respectively, a difference of 1.1 percent. The standard error of the mean for measured and simulated annual streamflow in the Bautista Creek subbasin was 299 and 217 acre-feet, respectively. Measured and simulated annual streamflows for the San Jacinto River above State Street near San Jacinto streamflow-gaging station (Poppet subbasin) for 1998 were 23,400 and 23,500 acre-feet, respectively, a difference of 0.4 percent. The simulated mean annual streamflow for the State Street gaging station at the outlet of the study basin and the simulated mean annual basin infiltration (combined infiltration from all the channels and land surfaces) were 8,720 and 41,600 acre-feet, respectively, for water years 1950-98. Simulated annual streamflow at the State Street gaging station ranged from 16.8 acre-feet in water year 1961 to 70,400 acre-feet in water year 1993, and simulated basin infiltration ranged from 2,770 acre-feet in water year 1961 to 149,000 acre-feet in water year 1983.The effects of increased urbanization on the hydrology of the study basin were evaluated by increasing the size of the effective impervious and non-effective impervious urban areas simulated in the calibrated rainfall-runoff model by 50 and 100 percent, respectively. The rainfall-runoff model simulated a long-term time series of monthly flows in and out of the channels and land surfaces using daily rainfall and potential evaporation data for water years 1950?98. Increasing the effective impervious and non-effective impervious urban areas by 100 percent resulted in a 5-percent increase in simulated mean annual streamflow at the State Street gaging station, and a 2.2-percent increase in simulated basin infiltration. Results of a frequency analysis of the simulated annual streamflow at the State Street gaging station showed that when effective impervious and non-effective impervious areas were increased 100 percent, simulated annual streamflow increased about 100 percent for low-flow conditions and was unchanged for high-flow conditions. The simulated increase in streamflow at the State Street gaging station potentially could infiltrate along the stream channel further downstream, outside of the model area.

Interannual rainfall variability over China in the MetUM GA6 and GC2 configurations

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas P.; Vidale, Pier Luigi; Turner, Andrew G.; Demory, Marie-Estelle; Guo, Liang

2018-05-01

Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyse the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ˜ 200, 90 and 40 km in the zonal direction at the equator, respectively) are analysed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China but improve with finer resolution and coupling. Empirical orthogonal teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal mean time series. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

Water Conservation Education with a Rainfall Simulator.

ERIC Educational Resources Information Center

Kok, Hans; Kessen, Shelly

1997-01-01

Describes a program in which a rainfall simulator was used to promote water conservation by showing water infiltration, water runoff, and soil erosion. The demonstrations provided a good background for the discussion of issues such as water conservation, crop rotation, and conservation tillage practices. The program raised awareness of…

Efficient Meshfree Large Deformation Simulation of Rainfall Induced Soil Slope Failure

NASA Astrophysics Data System (ADS)

Wang, Dongdong; Li, Ling

2010-05-01

An efficient Lagrangian Galerkin meshfree framework is presented for large deformation simulation of rainfall-induced soil slope failure. Detailed coupled soil-rainfall seepage equations are given for the proposed formulation. This nonlinear meshfree formulation is featured by the Lagrangian stabilized conforming nodal integration method where the low cost nature of nodal integration approach is kept and at the same time the numerical stability is maintained. The initiation and evolution of progressive failure in the soil slope is modeled by the coupled constitutive equations of isotropic damage and Drucker-Prager pressure-dependent plasticity. The gradient smoothing in the stabilized conforming integration also serves as a non-local regularization of material instability and consequently the present method is capable of effectively capture the shear band failure. The efficacy of the present method is demonstrated by simulating the rainfall-induced failure of two typical soil slopes.

Aerosol-induced changes in summer rainfall and circulation in the Australasian region: a study using single-forcing climate simulations

NASA Astrophysics Data System (ADS)

Rotstayn, L. D.; Jeffrey, S. J.; Collier, M. A.; Dravitzki, S. M.; Hirst, A. C.; Syktus, J. I.; Wong, K. K.

2012-02-01

We use a coupled atmosphere-ocean global climate model (CSIRO-Mk3.6) to investigate the roles of different forcing agents as drivers of summer rainfall trends in the Australasian region. Our results suggest that anthropogenic aerosols have contributed to the observed multi-decadal rainfall increase over north-western Australia. As part of the Coupled Model Intercomparison Project Phase 5 (CMIP5), we performed multiple 10-member ensembles of historical climate change, which are analysed for the period 1951-2010. The historical runs include ensembles driven by "all forcings" (HIST), all forcings except anthropogenic aerosols (NO_AA) and forcing only from long-lived greenhouse gases (GHGAS). Anthropogenic aerosol-induced effects in a warming climate are calculated from the difference of HIST minus NO_AA. We also compare a 10-member 21st century ensemble driven by Representative Concentration Pathway 4.5 (RCP4.5). Simulated aerosol-induced rainfall trends over the Indo-Pacific region for austral summer and boreal summer show a distinct contrast. In boreal summer, there is a southward shift of equatorial rainfall, consistent with the idea that anthropogenic aerosols have suppressed Asian monsoonal rainfall, and caused a southward shift of the local Hadley circulation. In austral summer, the aerosol-induced response more closely resembles a westward shift and strengthening of the upward branch of the Walker circulation, rather than a coherent southward shift of regional tropical rainfall. Thus the mechanism by which anthropogenic aerosols may affect Australian summer rainfall is unclear. Focusing on summer rainfall trends over north-western Australia (NWA), we find that CSIRO-Mk3.6 simulates a strong rainfall decrease in RCP4.5, whereas simulated trends in HIST are weak and insignificant during 1951-2010. The weak rainfall trends in HIST are due to compensating effects of different forcing agents: there is a significant decrease in GHGAS, offset by an aerosol-induced increase in HIST minus NO_AA. However, the magnitude of the observed NWA rainfall trend is not captured by the ensemble mean of HIST minus NO_AA, or by 440 unforced 60-yr trends calculated from a 500-yr pre-industrial control run. This suggests that the observed trend includes both a forced and unforced component. We investigate the mechanism of simulated and observed NWA rainfall changes by exploring changes in circulation over the Indo-Pacific region. The key circulation feature associated with the rainfall increase is a lower-tropospheric cyclonic circulation trend off the coast of NWA. In the model, it induces moisture convergence and upward motion over NWA. The cyclonic anomaly is present in trends calculated from HIST minus NO_AA and from reanalyses. Further analysis suggests that the cyclonic circulation trend in HIST minus NO_AA may be initiated as a Rossby wave response to positive convective heating anomalies south of the equator during November, when the aerosol-induced response of the model over the Indian Ocean still resembles that in boreal summer (i.e. a southward shift of equatorial rainfall). The aerosol-induced enhancement of the cyclonic circulation and associated monsoonal rainfall becomes progressively stronger from December to March, suggesting that there is a positive feedback between the source of latent heat (the Australian monsoon) and the cyclonic circulation. CSIRO-Mk3.6 indicates that anthropogenic aerosols may have masked greenhouse gas-induced changes in rainfall over NWA and in circulation over the wider Indo-Pacific region: simulated trends in RCP4.5 resemble a stronger version of those in GHGAS, and are very different from those in HIST. Further research is needed to better understand the mechanisms and the extent to which these findings are model-dependent.